Data Mining Practical Machine Learning Tools and Techniques 2nd Edition Ian H. Witten
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- 5. Data Mining Practical Machine Learning Tools and Techniques 2nd Edition Ian H. Witten Digital Instant Download Author(s): Ian H. Witten, Eibe Frank ISBN(s): 9780120884070, 0120884070 Edition: 2nd File Details: PDF, 5.36 MB Year: 2005 Language: english
- 7. Data Mining Practical Machine Learning Tools and Techniques
- 8. The Morgan Kaufmann Series in Data Management Systems Series Editor: Jim Gray, Microsoft Research Data Mining: Practical Machine Learning Tools and Techniques, Second Edition Ian H. Witten and Eibe Frank Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration Earl Cox Data Modeling Essentials, Third Edition Graeme C. Simsion and Graham C. Witt Location-Based Services Jochen Schiller and Agnès Voisard Database Modeling with Microsoft® Visio for Enterprise Architects Terry Halpin, Ken Evans, Patrick Hallock, and Bill Maclean Designing Data-Intensive Web Applications Stefano Ceri, Piero Fraternali, Aldo Bongio, Marco Brambilla, Sara Comai, and Maristella Matera Mining the Web: Discovering Knowledge from Hypertext Data Soumen Chakrabarti Advanced SQL: 1999—Understanding Object-Relational and Other Advanced Features Jim Melton Database Tuning: Principles, Experiments, and Troubleshooting Techniques Dennis Shasha and Philippe Bonnet SQL: 1999—Understanding Relational Language Components Jim Melton and Alan R. Simon Information Visualization in Data Mining and Knowledge Discovery Edited by Usama Fayyad, Georges G. Grinstein, and Andreas Wierse Transactional Information Systems: Theory, Algorithms, and the Practice of Concurrency Control and Recovery Gerhard Weikum and Gottfried Vossen Spatial Databases: With Application to GIS Philippe Rigaux, Michel Scholl, and Agnès Voisard Information Modeling and Relational Databases: From Conceptual Analysis to Logical Design Terry Halpin Component Database Systems Edited by Klaus R. Dittrich and Andreas Geppert Managing Reference Data in Enterprise Databases: Binding Corporate Data to the Wider World Malcolm Chisholm Data Mining: Concepts and Techniques Jiawei Han and Micheline Kamber Understanding SQL and Java Together: A Guide to SQLJ, JDBC, and Related Technologies Jim Melton and Andrew Eisenberg Database: Principles, Programming, and Performance, Second Edition Patrick O’Neil and Elizabeth O’Neil The Object Data Standard: ODMG 3.0 Edited by R. G. G. Cattell, Douglas K. Barry, Mark Berler, Jeff Eastman, David Jordan, Craig Russell, Olaf Schadow, Torsten Stanienda, and Fernando Velez Data on the Web: From Relations to Semistructured Data and XML Serge Abiteboul, Peter Buneman, and Dan Suciu Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations Ian H. Witten and Eibe Frank Joe Celko’s SQL for Smarties: Advanced SQL Programming, Second Edition Joe Celko Joe Celko’s Data and Databases: Concepts in Practice Joe Celko Developing Time-Oriented Database Applications in SQL Richard T. Snodgrass Web Farming for the Data Warehouse Richard D. Hackathorn Database Modeling & Design, Third Edition Toby J. Teorey Management of Heterogeneous and Autonomous Database Systems Edited by Ahmed Elmagarmid, Marek Rusinkiewicz, and Amit Sheth Object-Relational DBMSs: Tracking the Next Great Wave, Second Edition Michael Stonebraker and Paul Brown, with Dorothy Moore A Complete Guide to DB2 Universal Database Don Chamberlin Universal Database Management: A Guide to Object/Relational Technology Cynthia Maro Saracco Readings in Database Systems, Third Edition Edited by Michael Stonebraker and Joseph M. Hellerstein Understanding SQL’s Stored Procedures: A Complete Guide to SQL/PSM Jim Melton Principles of Multimedia Database Systems V. S. Subrahmanian Principles of Database Query Processing for Advanced Applications Clement T. Yu and Weiyi Meng Advanced Database Systems Carlo Zaniolo, Stefano Ceri, Christos Faloutsos, Richard T. Snodgrass, V. S. Subrahmanian, and Roberto Zicari Principles of Transaction Processing for the Systems Professional Philip A. Bernstein and Eric Newcomer Using the New DB2: IBM’s Object-Relational Database System Don Chamberlin Distributed Algorithms Nancy A. Lynch Active Database Systems: Triggers and Rules For Advanced Database Processing Edited by Jennifer Widom and Stefano Ceri Migrating Legacy Systems: Gateways, Interfaces & the Incremental Approach Michael L. Brodie and Michael Stonebraker Atomic Transactions Nancy Lynch, Michael Merritt, William Weihl, and Alan Fekete Query Processing For Advanced Database Systems Edited by Johann Christoph Freytag, David Maier, and Gottfried Vossen Transaction Processing: Concepts and Techniques Jim Gray and Andreas Reuter Building an Object-Oriented Database System: The Story of O2 Edited by François Bancilhon, Claude Delobel, and Paris Kanellakis Database Transaction Models For Advanced Applications Edited by Ahmed K. Elmagarmid A Guide to Developing Client/Server SQL Applications Setrag Khoshafian, Arvola Chan, Anna Wong, and Harry K. T. Wong The Benchmark Handbook For Database and Transaction Processing Systems, Second Edition Edited by Jim Gray Camelot and Avalon: A Distributed Transaction Facility Edited by Jeffrey L. Eppinger, Lily B. Mummert, and Alfred Z. Spector Readings in Object-Oriented Database Systems Edited by Stanley B. Zdonik and David Maier
- 9. Data Mining Practical Machine Learning Tools and Techniques, Second Edition Ian H. Witten Department of Computer Science University of Waikato Eibe Frank Department of Computer Science University of Waikato AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO MORGAN KAUFMANN PUBLISHERS IS AN IMPRINT OF ELSEVIER
- 10. Publisher: Diane Cerra Publishing Services Manager: Simon Crump Project Manager: Brandy Lilly Editorial Assistant: Asma Stephan Cover Design: Yvo Riezebos Design Cover Image: Getty Images Composition: SNP Best-set Typesetter Ltd., Hong Kong Technical Illustration: Dartmouth Publishing, Inc. Copyeditor: Graphic World Inc. Proofreader: Graphic World Inc. Indexer: Graphic World Inc. Interior printer: The Maple-Vail Book Manufacturing Group Cover printer: Phoenix Color Corp Morgan Kaufmann Publishers is an imprint of Elsevier. 500 Sansome Street, Suite 400, San Francisco, CA 94111 This book is printed on acid-free paper. © 2005 by Elsevier Inc. All rights reserved. Designations used by companies to distinguish their products are often claimed as trademarks or registered trademarks. In all instances in which Morgan Kaufmann Publishers is aware of a claim, the product names appear in initial capital or all capital letters. Readers, however, should contact the appropriate companies for more complete information regarding trademarks and registration. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopying, scanning, or otherwise— without prior written permission of the publisher. Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone: (+44) 1865 843830, fax: (+44) 1865 853333, e-mail: permissions@elsevier.com.uk. You may also complete your request on-line via the Elsevier homepage (http://elsevier.com) by selecting “Customer Support” and then “Obtaining Permissions.” Library of Congress Cataloging-in-Publication Data Witten, I. H. (Ian H.) Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank. – 2nd ed. p. cm. – (Morgan Kaufmann series in data management systems) Includes bibliographical references and index. ISBN: 0-12-088407-0 1. Data mining. I. Frank, Eibe. II. Title. III. Series. QA76.9.D343W58 2005 006.3–dc22 2005043385 For information on all Morgan Kaufmann publications, visit our Web site at www.mkp.com or www.books.elsevier.com Printed in the United States of America 05 06 07 08 09 5 4 3 2 1 Working together to grow libraries in developing countries www.elsevier.com | www.bookaid.org | www.sabre.org
- 11. Foreword Jim Gray, Series Editor Microsoft Research Technology now allows us to capture and store vast quantities of data. Finding patterns, trends, and anomalies in these datasets, and summarizing them with simple quantitative models, is one of the grand challenges of the infor- mation age—turning data into information and turning information into knowledge. There has been stunning progress in data mining and machine learning. The synthesis of statistics, machine learning, information theory, and computing has created a solid science, with a firm mathematical base, and with very powerful tools. Witten and Frank present much of this progress in this book and in the companion implementation of the key algorithms. As such, this is a milestone in the synthesis of data mining, data analysis, information theory, and machine learning. If you have not been following this field for the last decade, this is a great way to catch up on this exciting progress. If you have, then Witten and Frank’s presentation and the companion open-source workbench, called Weka, will be a useful addition to your toolkit. They present the basic theory of automatically extracting models from data, and then validating those models. The book does an excellent job of explaining the various models (decision trees, association rules, linear models, clustering, Bayes nets, neural nets) and how to apply them in practice. With this basis, they then walk through the steps and pitfalls of various approaches. They describe how to safely scrub datasets, how to build models, and how to evaluate a model’s predictive quality. Most of the book is tutorial, but Part II broadly describes how commercial systems work and gives a tour of the publicly available data mining workbench that the authors provide through a website. This Weka workbench has a graphical user interface that leads you through data mining tasks and has excellent data visualization tools that help understand the models. It is a great companion to the text and a useful and popular tool in its own right. v
- 12. This book presents this new discipline in a very accessible form: as a text both to train the next generation of practitioners and researchers and to inform lifelong learners like myself. Witten and Frank have a passion for simple and elegant solutions. They approach each topic with this mindset, grounding all concepts in concrete examples, and urging the reader to consider the simple techniques first, and then progress to the more sophisticated ones if the simple ones prove inadequate. If you are interested in databases, and have not been following the machine learning field, this book is a great way to catch up on this exciting progress. If you have data that you want to analyze and understand, this book and the asso- ciated Weka toolkit are an excellent way to start. vi FOREWORD
- 13. Contents Foreword v Preface xxiii Updated and revised content xxvii Acknowledgments xxix Part I Machine learning tools and techniques 1 1 What’s it all about? 3 1.1 Data mining and machine learning 4 Describing structural patterns 6 Machine learning 7 Data mining 9 1.2 Simple examples: The weather problem and others 9 The weather problem 10 Contact lenses: An idealized problem 13 Irises: A classic numeric dataset 15 CPU performance: Introducing numeric prediction 16 Labor negotiations: A more realistic example 17 Soybean classification: A classic machine learning success 18 1.3 Fielded applications 22 Decisions involving judgment 22 Screening images 23 Load forecasting 24 Diagnosis 25 Marketing and sales 26 Other applications 28 vii
- 14. 1.4 Machine learning and statistics 29 1.5 Generalization as search 30 Enumerating the concept space 31 Bias 32 1.6 Data mining and ethics 35 1.7 Further reading 37 2 Input: Concepts, instances, and attributes 41 2.1 What’s a concept? 42 2.2 What’s in an example? 45 2.3 What’s in an attribute? 49 2.4 Preparing the input 52 Gathering the data together 52 ARFF format 53 Sparse data 55 Attribute types 56 Missing values 58 Inaccurate values 59 Getting to know your data 60 2.5 Further reading 60 3 Output: Knowledge representation 61 3.1 Decision tables 62 3.2 Decision trees 62 3.3 Classification rules 65 3.4 Association rules 69 3.5 Rules with exceptions 70 3.6 Rules involving relations 73 3.7 Trees for numeric prediction 76 3.8 Instance-based representation 76 3.9 Clusters 81 3.10 Further reading 82 viii CONTENTS
- 15. 4 Algorithms: The basic methods 83 4.1 Inferring rudimentary rules 84 Missing values and numeric attributes 86 Discussion 88 4.2 Statistical modeling 88 Missing values and numeric attributes 92 Bayesian models for document classification 94 Discussion 96 4.3 Divide-and-conquer: Constructing decision trees 97 Calculating information 100 Highly branching attributes 102 Discussion 105 4.4 Covering algorithms: Constructing rules 105 Rules versus trees 107 A simple covering algorithm 107 Rules versus decision lists 111 4.5 Mining association rules 112 Item sets 113 Association rules 113 Generating rules efficiently 117 Discussion 118 4.6 Linear models 119 Numeric prediction: Linear regression 119 Linear classification: Logistic regression 121 Linear classification using the perceptron 124 Linear classification using Winnow 126 4.7 Instance-based learning 128 The distance function 128 Finding nearest neighbors efficiently 129 Discussion 135 4.8 Clustering 136 Iterative distance-based clustering 137 Faster distance calculations 138 Discussion 139 4.9 Further reading 139 CONTENTS ix
- 16. 5 Credibility: Evaluating what’s been learned 143 5.1 Training and testing 144 5.2 Predicting performance 146 5.3 Cross-validation 149 5.4 Other estimates 151 Leave-one-out 151 The bootstrap 152 5.5 Comparing data mining methods 153 5.6 Predicting probabilities 157 Quadratic loss function 158 Informational loss function 159 Discussion 160 5.7 Counting the cost 161 Cost-sensitive classification 164 Cost-sensitive learning 165 Lift charts 166 ROC curves 168 Recall–precision curves 171 Discussion 172 Cost curves 173 5.8 Evaluating numeric prediction 176 5.9 The minimum description length principle 179 5.10 Applying the MDL principle to clustering 183 5.11 Further reading 184 6 Implementations: Real machine learning schemes 187 6.1 Decision trees 189 Numeric attributes 189 Missing values 191 Pruning 192 Estimating error rates 193 Complexity of decision tree induction 196 From trees to rules 198 C4.5: Choices and options 198 Discussion 199 6.2 Classification rules 200 Criteria for choosing tests 200 Missing values, numeric attributes 201 x CONTENTS
- 17. Generating good rules 202 Using global optimization 205 Obtaining rules from partial decision trees 207 Rules with exceptions 210 Discussion 213 6.3 Extending linear models 214 The maximum margin hyperplane 215 Nonlinear class boundaries 217 Support vector regression 219 The kernel perceptron 222 Multilayer perceptrons 223 Discussion 235 6.4 Instance-based learning 235 Reducing the number of exemplars 236 Pruning noisy exemplars 236 Weighting attributes 237 Generalizing exemplars 238 Distance functions for generalized exemplars 239 Generalized distance functions 241 Discussion 242 6.5 Numeric prediction 243 Model trees 244 Building the tree 245 Pruning the tree 245 Nominal attributes 246 Missing values 246 Pseudocode for model tree induction 247 Rules from model trees 250 Locally weighted linear regression 251 Discussion 253 6.6 Clustering 254 Choosing the number of clusters 254 Incremental clustering 255 Category utility 260 Probability-based clustering 262 The EM algorithm 265 Extending the mixture model 266 Bayesian clustering 268 Discussion 270 6.7 Bayesian networks 271 Making predictions 272 Learning Bayesian networks 276 CONTENTS xi
- 18. Specific algorithms 278 Data structures for fast learning 280 Discussion 283 7 Transformations: Engineering the input and output 285 7.1 Attribute selection 288 Scheme-independent selection 290 Searching the attribute space 292 Scheme-specific selection 294 7.2 Discretizing numeric attributes 296 Unsupervised discretization 297 Entropy-based discretization 298 Other discretization methods 302 Entropy-based versus error-based discretization 302 Converting discrete to numeric attributes 304 7.3 Some useful transformations 305 Principal components analysis 306 Random projections 309 Text to attribute vectors 309 Time series 311 7.4 Automatic data cleansing 312 Improving decision trees 312 Robust regression 313 Detecting anomalies 314 7.5 Combining multiple models 315 Bagging 316 Bagging with costs 319 Randomization 320 Boosting 321 Additive regression 325 Additive logistic regression 327 Option trees 328 Logistic model trees 331 Stacking 332 Error-correcting output codes 334 7.6 Using unlabeled data 337 Clustering for classification 337 Co-training 339 EM and co-training 340 7.7 Further reading 341 xii CONTENTS
- 19. 8 Moving on: Extensions and applications 345 8.1 Learning from massive datasets 346 8.2 Incorporating domain knowledge 349 8.3 Text and Web mining 351 8.4 Adversarial situations 356 8.5 Ubiquitous data mining 358 8.6 Further reading 361 Part II The Weka machine learning workbench 363 9 Introduction to Weka 365 9.1 What’s in Weka? 366 9.2 How do you use it? 367 9.3 What else can you do? 368 9.4 How do you get it? 368 10 The Explorer 369 10.1 Getting started 369 Preparing the data 370 Loading the data into the Explorer 370 Building a decision tree 373 Examining the output 373 Doing it again 377 Working with models 377 When things go wrong 378 10.2 Exploring the Explorer 380 Loading and filtering files 380 Training and testing learning schemes 384 Do it yourself: The User Classifier 388 Using a metalearner 389 Clustering and association rules 391 Attribute selection 392 Visualization 393 10.3 Filtering algorithms 393 Unsupervised attribute filters 395 Unsupervised instance filters 400 Supervised filters 401 CONTENTS xiii
- 20. 10.4 Learning algorithms 403 Bayesian classifiers 403 Trees 406 Rules 408 Functions 409 Lazy classifiers 413 Miscellaneous classifiers 414 10.5 Metalearning algorithms 414 Bagging and randomization 414 Boosting 416 Combining classifiers 417 Cost-sensitive learning 417 Optimizing performance 417 Retargeting classifiers for different tasks 418 10.6 Clustering algorithms 418 10.7 Association-rule learners 419 10.8 Attribute selection 420 Attribute subset evaluators 422 Single-attribute evaluators 422 Search methods 423 11 The Knowledge Flow interface 427 11.1 Getting started 427 11.2 The Knowledge Flow components 430 11.3 Configuring and connecting the components 431 11.4 Incremental learning 433 12 The Experimenter 437 12.1 Getting started 438 Running an experiment 439 Analyzing the results 440 12.2 Simple setup 441 12.3 Advanced setup 442 12.4 The Analyze panel 443 12.5 Distributing processing over several machines 445 xiv CONTENTS
- 21. 13 The command-line interface 449 13.1 Getting started 449 13.2 The structure of Weka 450 Classes, instances, and packages 450 The weka.core package 451 The weka.classifiers package 453 Other packages 455 Javadoc indices 456 13.3 Command-line options 456 Generic options 456 Scheme-specific options 458 14 Embedded machine learning 461 14.1 A simple data mining application 461 14.2 Going through the code 462 main() 462 MessageClassifier() 462 updateData() 468 classifyMessage() 468 15 Writing new learning schemes 471 15.1 An example classifier 471 buildClassifier() 472 makeTree() 472 computeInfoGain() 480 classifyInstance() 480 main() 481 15.2 Conventions for implementing classifiers 483 References 485 Index 505 About the authors 525 CONTENTS xv
- 23. List of Figures Figure 1.1 Rules for the contact lens data. 13 Figure 1.2 Decision tree for the contact lens data. 14 Figure 1.3 Decision trees for the labor negotiations data. 19 Figure 2.1 A family tree and two ways of expressing the sister-of relation. 46 Figure 2.2 ARFF file for the weather data. 54 Figure 3.1 Constructing a decision tree interactively: (a) creating a rectangular test involving petallength and petalwidth and (b) the resulting (unfinished) decision tree. 64 Figure 3.2 Decision tree for a simple disjunction. 66 Figure 3.3 The exclusive-or problem. 67 Figure 3.4 Decision tree with a replicated subtree. 68 Figure 3.5 Rules for the Iris data. 72 Figure 3.6 The shapes problem. 73 Figure 3.7 Models for the CPU performance data: (a) linear regression, (b) regression tree, and (c) model tree. 77 Figure 3.8 Different ways of partitioning the instance space. 79 Figure 3.9 Different ways of representing clusters. 81 Figure 4.1 Pseudocode for 1R. 85 Figure 4.2 Tree stumps for the weather data. 98 Figure 4.3 Expanded tree stumps for the weather data. 100 Figure 4.4 Decision tree for the weather data. 101 Figure 4.5 Tree stump for the ID code attribute. 103 Figure 4.6 Covering algorithm: (a) covering the instances and (b) the decision tree for the same problem. 106 Figure 4.7 The instance space during operation of a covering algorithm. 108 Figure 4.8 Pseudocode for a basic rule learner. 111 Figure 4.9 Logistic regression: (a) the logit transform and (b) an example logistic regression function. 122 xvii
- 24. Figure 4.10 The perceptron: (a) learning rule and (b) representation as a neural network. 125 Figure 4.11 The Winnow algorithm: (a) the unbalanced version and (b) the balanced version. 127 Figure 4.12 A kD-tree for four training instances: (a) the tree and (b) instances and splits. 130 Figure 4.13 Using a kD-tree to find the nearest neighbor of the star. 131 Figure 4.14 Ball tree for 16 training instances: (a) instances and balls and (b) the tree. 134 Figure 4.15 Ruling out an entire ball (gray) based on a target point (star) and its current nearest neighbor. 135 Figure 4.16 A ball tree: (a) two cluster centers and their dividing line and (b) the corresponding tree. 140 Figure 5.1 A hypothetical lift chart. 168 Figure 5.2 A sample ROC curve. 169 Figure 5.3 ROC curves for two learning methods. 170 Figure 5.4 Effects of varying the probability threshold: (a) the error curve and (b) the cost curve. 174 Figure 6.1 Example of subtree raising, where node C is “raised” to subsume node B. 194 Figure 6.2 Pruning the labor negotiations decision tree. 196 Figure 6.3 Algorithm for forming rules by incremental reduced-error pruning. 205 Figure 6.4 RIPPER: (a) algorithm for rule learning and (b) meaning of symbols. 206 Figure 6.5 Algorithm for expanding examples into a partial tree. 208 Figure 6.6 Example of building a partial tree. 209 Figure 6.7 Rules with exceptions for the iris data. 211 Figure 6.8 A maximum margin hyperplane. 216 Figure 6.9 Support vector regression: (a) e = 1, (b) e = 2, and (c) e = 0.5. 221 Figure 6.10 Example datasets and corresponding perceptrons. 225 Figure 6.11 Step versus sigmoid: (a) step function and (b) sigmoid function. 228 Figure 6.12 Gradient descent using the error function x2 + 1. 229 Figure 6.13 Multilayer perceptron with a hidden layer. 231 Figure 6.14 A boundary between two rectangular classes. 240 Figure 6.15 Pseudocode for model tree induction. 248 Figure 6.16 Model tree for a dataset with nominal attributes. 250 Figure 6.17 Clustering the weather data. 256 xviii LIST OF FIGURES
- 25. Figure 6.18 Hierarchical clusterings of the iris data. 259 Figure 6.19 A two-class mixture model. 264 Figure 6.20 A simple Bayesian network for the weather data. 273 Figure 6.21 Another Bayesian network for the weather data. 274 Figure 6.22 The weather data: (a) reduced version and (b) corresponding AD tree. 281 Figure 7.1 Attribute space for the weather dataset. 293 Figure 7.2 Discretizing the temperature attribute using the entropy method. 299 Figure 7.3 The result of discretizing the temperature attribute. 300 Figure 7.4 Class distribution for a two-class, two-attribute problem. 303 Figure 7.5 Principal components transform of a dataset: (a) variance of each component and (b) variance plot. 308 Figure 7.6 Number of international phone calls from Belgium, 1950–1973. 314 Figure 7.7 Algorithm for bagging. 319 Figure 7.8 Algorithm for boosting. 322 Figure 7.9 Algorithm for additive logistic regression. 327 Figure 7.10 Simple option tree for the weather data. 329 Figure 7.11 Alternating decision tree for the weather data. 330 Figure 10.1 The Explorer interface. 370 Figure 10.2 Weather data: (a) spreadsheet, (b) CSV format, and (c) ARFF. 371 Figure 10.3 The Weka Explorer: (a) choosing the Explorer interface and (b) reading in the weather data. 372 Figure 10.4 Using J4.8: (a) finding it in the classifiers list and (b) the Classify tab. 374 Figure 10.5 Output from the J4.8 decision tree learner. 375 Figure 10.6 Visualizing the result of J4.8 on the iris dataset: (a) the tree and (b) the classifier errors. 379 Figure 10.7 Generic object editor: (a) the editor, (b) more information (click More), and (c) choosing a converter (click Choose). 381 Figure 10.8 Choosing a filter: (a) the filters menu, (b) an object editor, and (c) more information (click More). 383 Figure 10.9 The weather data with two attributes removed. 384 Figure 10.10 Processing the CPU performance data with M5¢. 385 Figure 10.11 Output from the M5¢ program for numeric prediction. 386 Figure 10.12 Visualizing the errors: (a) from M5¢ and (b) from linear regression. 388 LIST OF FIGURES xix
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- 27. Christ, trembling, shaking, sobbing. Praying aloud, he said to the Redeemer: 'O Lamb of God, forgive me! I am ungrateful and ignorant, a miserable sinner. Forgive me, forgive! Do not make me suffer for my sins. Do me this grace for the sake of my languishing, dying daughter. I am unworthy, but bless me for her sake. O sorrowful Virgin, who hast suffered so much, understand and help me! Send a vision to Sister Maria degli Angioli. O blessed spirit, Beatrice Cavalcanti, my saintly wife, if I caused you sorrow, forgive me! Forgive me if I shortened your life! Do it for your daughter's sake: save your family. Appear to your daughter—she is innocent and good; tell her the words to save us, blessed spirit! blessed spirit!' The girl, who beard it all, was so frightened she fled with her eyes shut, holding her head. When she got to her room, she thought she heard a deep, sad sigh behind her, and felt a light hand on her shoulder. Mad with terror, she could not cry out; she fell her whole length on the ground, and lay as if she were dead.
- 28. CHAPTER IV DR. AMATI Not once for a month past had Dr. Antonio Amati seen that thoughtful, delicate girl's face between the yellowish old curtains in the balcony opposite his study window, which looked into the big court of Rossi Palace, formerly Cavalcanti. Two years had passed from the day that one of the youngest, though one of the most distinguished, Naples doctors had come to take up his abode there alone, with one man-servant and a housekeeper, but bringing a crowd of old and new patients after him, filling the spacious, but rather dark, stairs with a going and coming of busy, preoccupied people. From the very first day he had noticed opposite his study window in passing that pure oval, the faintly pink, delicate complexion, those proud, soft eyes, that touched the heart from their gentleness. He saw all that at once, in spite of the windows opposite being dull from old age and her appearing for a short time only. He was a quick observer; in fact, a great part of his medical skill was owing to his quick glance, his lively, true, deep intuition. 'A heart with no sun,' he said to himself, turning round to put his heavy scientific volumes into his carved oak shelves. Nor was he surprised when the Rossi Palace door-keeper, humbly consulting him under the portico, as he got into his carriage for his round of afternoon visits, about a feverish illness that had inflamed her spleen, told him, amongst a flood of other gossip, that that angel
- 29. opposite his balcony was Lady Bianca Maria Cavalcanti, a lady of high birth, but reduced in circumstances, poor girl, not by her own fault.... 'But perhaps she will become a nun,' the woman ended up. 'A heart with no sun,' Dr. Antonio Amati thought again as he went away, after prescribing for the sickly, talkative door-keeper. But he had no time to remark or think of aristocratic ladies come down by bad luck, or their parents' sins, to obscurity and wretchedness; he could not let his fancy linger long on that melancholy life alongside of his, but so different from it. He was a silent, energetic man of action; a Southerner not fond of words, who put into his daily work all the strength other Southerners put into dreams, talk, and long speeches, accustoming himself to this self- government, calling up every day the violence of his fiery temper to conquer it by strength of will, and make use of it for scientific practical work, keeping always in touch with life, books, and suffering humanity, which at thirty-five had made him famous. He was proud of his great reputation, but not conceited, though lucky fortune had not made him mean or lowered him. No, he could not dream about Bianca Maria's lily face; too many around him were ill of typhus, smallpox, consumption, and a hundred other severe, almost incurable, illnesses that required his daily help and energies. Too many people called to him, implored him, stretched out their hands for help, besieging his waiting-room and the hospital door, watching for him at the University and other sick people's doors patiently and submissively, as if waiting for a saviour. Too many were suffering, sick and dying, for him to dream about that slight apparition, and admire the pale, thoughtful face bending under the weight of black tresses. Still, through that life of useful work for himself and others, through the seeming hardness, hurry, even scientific brutality of his constant activity, which was made up for by his noble daily sacrifices, that silently attractive figure pleased Dr. Antonio Amati's fancy. Gradually it took its place each morning among the things he admired and liked to find in their places every day: his books, old leather note- books, some mementos of childhood and youth, a wax model of his
- 30. dead sister's little hand, an old photograph of his mother, who lived in Campobasso province, a local accent he had not lost, in spite of living eighteen years in Naples and his travels in France and Germany. Bianca Maria came into this harmonious atmosphere, that gently satisfied this strong man's eyes and heart. Antonio Amati did not try to see her oftener, nor to know and speak to her; it was enough to see her in the early morning, behind her balcony windows, look down vaguely into the dull, damp court, then disappear as slowly as she came—a quiet, solitary figure, not sorrowful, but not smiling. Between one patient going and another coming, Dr. Amati got up from his desk, and went as far as the balcony; in one or other of these little walks, that seemed to serve him as a pause, a rest, a distraction between one bit of work finished and another begun, he caught sight of Bianca Maria's pale, thoughtful face; and for two years that satisfied him. It is true that sometimes in these two years he had met her on the stairs, or in the Rossi Palace dark entrance, with her father or Margherita; he took off his hat, and she acknowledged his bow unsmilingly. She, too, knew him well, seeing him every day; but she looked him in the face frankly, with none of that extreme reserve, half smile, half sham indifference, or any of the little coquetries of commonplace girls. Frankly and innocently she looked at him a minute, returned his bow, and then her proud, gentle eyes took their vague thoughtful expression again. They did not make daily appointments to see each other—he was too serious, too engrossed in duty to do so, and she was a simple creature, living too solitary an inward life to think of it—only they saw each other every day, and got accustomed to it. 'But perhaps she is to be a nun,' the door-keeper repeated sometimes. She had got over her illness, and employed herself over other people's ailments, moral and physical. But the doctor walked on without replying, thinking of the sad chorus of lamentations that went on around him, from rich and poor, for real, present, imminent sorrows, almost hopeless to cure, but
- 31. worthy of his courage and talent to attempt. Still, in that damp, south-east wind this autumn morning, whilst bad coughs, heart complaints, fevers came by turns dolefully in his list of cases, this sickly atmosphere of bad weather in Naples making them worse, he had, as usual, filled up his leisure by going to the balcony; and not seeing Bianca Maria, he felt annoyance of a latent, indefinite kind, which every new country or suburban patient made him forget; but it came back when the patient left. The forenoon passed in the gloom of the great writing-table, covered with maroon; of these colourless, anxious faces held up to him; these weak, complaining voices; lean breasts, or flabby with unhealthy fat, that were bared for him to find traces of consumption or atrophy, with wheezing, funereal coughs. Never had he felt the disagreeables of his profession so much as that day. Bianca Maria did not appear. 'She is ill,' he thought momentarily. Having thought of this, he felt as sure as if someone had told him or if he had seen her ill himself. She was sick. He at once thought of helping her, with that instinct to save life all great doctors have. He thought it over a minute; but his mind came back to the realities of life at once. It was folly to be taken up about a person he did not know, and who probably did not care to have him. If they needed his skill, they would have called him. For all that, he was sure Bianca Maria was ill. But another patient came into the room. There were two, rather—a youth and a girl of the lower class. He recognised the girl at once from her hollow, worn face and sad, black-encircled eyes, the lock of untidy hair. He had cured her of typhoid at San Raffaele hospital, when the epidemic was raging in Naples. 'Is it you, Carmela?' 'Good-day to you, sir,' said the girl, rushing forward to kiss the doctor's hand, which he quickly drew back. 'Are you ill?' he asked. 'As if I was ill,' she said, smiling, in a faint, melancholy way, while the doctor was trying to recognise the young fellow's face. 'I am
- 32. going to have a misfortune that is worse than an illness, sir.' She turned to her companion as she spoke, and called out: 'Raffaé!' Then Amati saw the young fellow in all the guappesca style of bell- trousers, small folded cap, silver chain with a bit of coral, shiny squeaking shoes, and the half-scampish, impudent look of a lad of twenty who has given up the knife, the traditional sfarziglia of his ancestors in the Camorra, for the modern revolver. 'This is my lover, sir,' she said, humbly and proudly, whilst Raffaele looked straight before him, as if it was not his business. She gave the youth so intense a look, so full of tenderness and passion, that the doctor had to restrain an impatient shrug. 'Is he ill?' he asked. 'No, sir; he is very well, thank God! But he has—that is to say, we have—another misfortune coming on us; or, indeed, it is my misfortune, as I must lose him. They want to take him for the levy,' said she, in a trembling voice, her eyes filling with tears. 'That is natural enough,' answered the doctor, smiling. 'How can you say so, sir? It is infamous of the Government to take a fine lad that ought to marry. If you won't help me, sir, what will I do?' 'And what can I do?' Raffaele, in the meanwhile, stood with one hand at his side, hanging his hat between two fingers; sometimes he looked Carmela up and down absent-mindedly and haughtily, as if it was out of mere good- nature he allowed her to look after his affairs; then he cast an oblique but dignified glance on the doctor. 'You are so kind, sir,' Carmela murmured. 'I want you to give Raffaele a medicine to make him ill, and get him scratched off the list.' 'It is impossible, my dear girl.' 'Why so, sir?'
- 33. 'Because there are no such miraculous medicines.' 'Oh, sir, you mean you don't wish to do me this kindness. Think if they take him for three years!—three years! What could I do without him for three years? And, then, he won't go, sir! If you knew what he says——' 'I told her,' Raffaele interrupted emphatically, pulling down his waistcoat, a common guappa trick, 'that if they take me by force, we will hold a little shooting; someone will be wounded, they take me to prison, and what happens? A year's imprisonment at most. I must go to San Francesco some day, at any rate.' 'Don't speak that way—don't say that!' she called out in admiring terror. 'Beg the professor to give you the medicine.' 'Are you to be married soon?' asked the doctor, who no longer wondered at anything, from knowing the people so well. 'Very soon,' Carmela answered by herself, while Raffaele looked before him. 'When are you to be?' 'When we get the terno,' she retorted, quietly and with certainty. 'Then, not for some time yet,' the doctor replied, laughing. 'No, no, sir; Don Pasqualino De Feo, the medium, has promised me a safe number. We will be married very soon. But you must get Raffaele off.' 'There is no need of my services. Raffaele will be rejected, because he has a narrow chest,' concluded the doctor, after looking carefully at the dandy. 'Do you say so, really?' 'Really it is so.' 'God bless you, sir! if I had to have this sorrow too, I would die. So many sorrows—so many,' she said in a low tone, pulling up her
- 34. shabby shawl on her shoulders; 'I am the mother of sorrows,' she added, with a sad smile. 'Good-day, sir,' said Raffaele. 'When you come to Mercato or Pendino district, ask for Raffaele—I am called Farfariello—and let me serve you in any way I can.' 'Thank you—thank you,' replied the doctor, sending them off. The two again repeated their farewells on their way out—she with a smile on her suffering face, he with the look of a man that despises women. Other patients came in requiring his medical skill up to twelve o'clock, when the time for receiving visits was over. Bianca Maria had not appeared. She was ill, therefore. He took breakfast very hurriedly, and ordered the coachman to bring round the carriage to go to the hospital at one o'clock. The day was getting more and more unpleasant, from the scirocco's damp, ill- smelling breath. He went out quickly, as he was rather late, and on the stairs, half in shadow, he met Bianca Maria going down also, with Margherita, her maid. 'Then, she is not ill,' thought the doctor. But with the sharp eyes of an observing man, who finds out the truth from the slightest symptoms, he saw the girl was walking undecidedly; her face, as she looked up to bow, was intensely pale, so that again his medical instinct was to help her. He was just going to speak, to ask her brusquely where the pain was, but her proud, gentle eyes were cast down again absent-mindedly; her mouth had that severe silent look that imposes silence on others. She disappeared without his saying anything. Dr. Amati shrugged his shoulders as he got into the carriage, and buried himself in a medical journal, as he did every day, to fill up even the short drive usefully. The carriage rolled along silently over the thin layer of mud; the damp obscured the windows, and the doctor felt the scirocco in himself and in the air. Even the hospital could not soothe the doctor's discomfort, though to take his thoughts off it he went deeper into practical medical work and scientific explanations to the
- 35. pupils than usual. He went backwards and forwards from one bed to another, followed by a crowd of youths, taller than any of them, with an obstinate man's short forehead, marked by two perpendicular lines, from a constant frown, showing a strong will and absorption in his work; his thick brush of black hair was roughly set on his forehead, with some white tufts showing already. So great was his activity of thought, words, and action, one expected to see the smoke of a volcano coming out. His orders to the assistants and his class, even to the nuns, were given harshly; they all obeyed quickly and silently, feeling respect for the iron will, in spite of his rough commands, mingled with admiration for the man who was looked on as a saviour. Even the room he had charge of looked more melancholy and wretched that day than ever; the dulness of the air saddened the invalids, the heavy, evil-smelling damp made them feel their pains more. A whispered lament, like a long, laboured breath, was heard from one end of the room to the other, and the sick folks' pale faces got yellow in that ghastly light; their emaciated hands on the coverlets looked like wax. In spite of trying to stun himself with work and words, Dr. Amati felt the disagreeables of his profession more than ever. Through that long, narrow room, full of beds in a row, and yellow, suffering faces, and the constant smell of phenic acid; through the scirocco mist and damp, that made even the nuns' pink cheeks bloodless-looking, he had a dream, a passing vision of a sunny, green, warm, clear, sweet- smelling country place, and his heart ached for this idyll, come and gone in a moment. 'Good-bye, gentlemen,' Amati said brusquely to the students, dismissing them. They knew that when he so greeted them he wished to be left alone; they knew, they understood, the Professor was in a bad humour; they let him go. One of the ambulance men brought him two or three letters that came while he was going his rounds; they were summonses, urgent letters from sick people longing for him, from a father who had lost his head over a son's illness, from
- 36. despairing women. He shook his head as he read them, as if he had lost confidence—as if all humanity sorrowing discouraged him. He went—yes, he went; but he felt very tired, which must have come from his mind, for he had worked much less than usual. He was going along absent-mindedly, when a shadow rose before him on the hospital stairs. It was a poor woman, of no particular age, with sparse grayish hair, black teeth, prominent cheek-bones, her clothes torn and dirty, whilst the slumbering babe she carried was clean, though meanly clad. 'Sir—please, sir!' she called out in a crying voice, seeing the doctor was going on without troubling himself about her. 'What do you want? Who are you?' the doctor asked roughly, without looking at her. 'I am Annarella, Carmela's sister—you saved her life,' said Gaetano the glove-cutter's wretched wife. 'Your sister in the morning, and now you!' the doctor impatiently exclaimed. 'Not for me, sir—not for me,' the gambler's wife said in a low tone. 'I can die. I don't signify. I do so little in the world I can't even find bread for my children.' 'Get out of the way—get out of the way.' 'It is for this little creature, for my sick son, sir;' and she bent to kiss the little slumberer's forehead. 'I don't know what is the matter, but he falls off every day, and I don't know what to give him. Cure him for me, sir.' The doctor leant over the little invalid, with its pretty, delicate, pallid face, purple eyelids, hardly perceptible breathing, and lips slightly apart; he touched its forehead and hands, then looked at the mother. 'You give it milk?' he asked shortly. 'Yes, sir,' said she, with a slight smile of motherly content.
- 37. 'How many months old is he?' 'Eighteen months.' 'And you still suckle him? You are all the same, you Naples women. Wean him at once.' 'Oh, sir!' she exclaimed, quite alarmed. 'Wean him,' he repeated. 'What am I to give him?' she said, almost sobbing. 'I often want bread for myself and the other two, but never milk. Must this poor little soul die of hunger too?' 'Does your husband not work?' asked the doctor ponderingly. 'Yes, sir, he does work,' she said, shaking her head. 'Does he keep another woman?' 'No, sir.' 'What does he do, then?' 'He plays at the lottery.' 'I understand. Wean the child. He has fever. Your milk poisons him.' After gazing at the doctor and her child, she just said 'Jesus' in a whisper, and a sob burst out from her motherly breast. Amati wrote out a prescription in pencil on a leaf of his pocket-book. He went down the stairs, followed by Annarella, whose tears fell over the child's face, her dull sobs following him in lamentation. 'This is the prescription; here are five francs to get it with,' said the doctor, motioning to her not to thank him. She looked at him with stupefied eyes while he crossed the big cold hospital court to his carriage; she began to cry again when she was alone; gazing on the baby, the prescription in her hand shook—it was so bitter for her to think of having poisoned her son with her milk.
- 38. 'It must be cholera,' she kept saying to herself, for among Naples common folk stomach disorders are often called cholera. Dr. Amati shook his head again energetically, as if he had lost confidence altogether in the saving of humanity. As he was opening the carriage door to get in, a woman who had been chattering with the hospital porter came up to speak to him. It was a woman in black, with a nun's shawl, and black silk kerchief on her head, tied under the chin. She had coal-black eyes in a pale face—eyes used to the shade and silence. She spoke very low. 'Sir, would you come with me to do an urgent kindness?' 'I am busy,' the doctor grumbled, getting into his carriage. 'The person is very, very ill.' 'All the people I have to see are ill.' 'She is near here, sir, in the Sacramentiste convent. I was sent to the hospital to find a doctor. I can't go back without one ... she is so very ill....' 'Dr. Caramanna is still up there—ask for him,' Amati retorted. 'Is it a nun that is ill?' he then added. 'The Sacramentistes are cloistered; they can't call men into the convent,' said the servant, pursing her lips. 'It is someone who got ill in the convent parlour, not belonging to the convent....' 'I will come,' Amati said quickly. He pushed the servant into the carriage, got in and shut the door. The carriage rolled along the Anticaglia road, which is so dark, muddy, and wretched from old age; and they did not say a word to each other in the short drive. The carriage stopped before the convent gate; instead of ringing the bell, the servant opened the door with a key. The doctor and she first crossed an icy court overlooked by a number of windows with green jalousies, then a corridor with pillars along the court; complete solitude and silence was everywhere. They went into a vast room on the ground-floor.
- 39. Along the white-washed walls were straw chairs, nothing else; at the end a big table, with a seat for the porter lay Sister. A crucifix was nailed on one wall. Along the other were two narrow gratings with a wheel in the middle, to speak through and pass things to the nuns. Near this wall, on three chairs, a woman's form was stretched out; another woman was kneeling and bending over her face. Before the doctor got as far as the woman lying down, the servant went up to the grating and spoke: 'Praise to the Holy Sacrament——' 'Now and for ever,' a very feeble voice answered from inside, as if it came out of a deep cave. 'Is the doctor here?' 'Yes, Sister Maria.' 'That is well;' and a long, feverish sigh was heard. In the meantime Dr. Amati had gone up to the fainting girl. Margherita was bathing her forehead with a handkerchief steeped in vinegar, and whispering: 'My darling! my darling!' The doctor put his hat on the ground, and knelt down too, to examine the fainting girl. He felt her pulse, and gently raised one eyelid; the eye was glassy. 'How long has she been like this?' he asked in a whisper, rubbing her icy hands. 'Half an hour,' the old woman replied. 'What have you done for her?' 'Nothing but use the vinegar. They gave it to me through the wheel; they have nothing else; it is a convent under strict rules.' 'Does she often faint?' 'Last night ... she had another swoon. I found her on the ground in her room. I called my master.' 'Did she recover of herself ... last night?' 'Yes.'
- 40. 'Had she got a fright?' 'I don't know ... I don't think so,' she said in a hesitating way. They were speaking in a whisper, whilst the servant stood right at the grating, as if mounting guard. 'Is she better?' the feeble voice inside asked. 'Just the same,' replied the servant in a monotonous voice. 'Oh God!' the voice called out in anguish. Meanwhile the doctor bent down to hear the breathing better. He seemed thoughtful and preoccupied. Margherita looked at him with despairing eyes. 'Did she get a fright, half an hour ago, in here?' he began again to ask, whilst he carefully raised Bianca's head and placed it against his breast. 'No! ... certainly not!' Margherita whispered. 'I was in church. I did not hear what was said; they called to me.' 'Who is that nun?' he asked, pointing to the grating. 'It is Sister Maria degli Angioli—the aunt.' Then he got up and went to the grating. The serving Sister pursed up her lips to remind him of the cloistral rule, almost as if she wanted to prevent any conversation between him and the nun. 'Sister Maria——' he said very gently. 'Now and for ever,' the feeble voice said hurriedly, hearing a man's voice. 'Has your niece had a fright?' Silence on the other side. 'Did she tell you of anything disagreeable that had happened to her?' 'Yes, yes!' the voice breathed out, trembling. 'Can you tell me what it was about?'
- 41. 'No, no!' she went on quickly, still trembling. 'Something very sad ... I can't tell you.' 'Very well—thank you,' he whispered, getting up again. 'How is she? Are you giving her anything?' the Sister's voice asked. 'We are going to take her to the house. Nothing can be done here.' 'We are poor nuns,' the Sister murmured. 'How will you carry her?' 'In the carriage,' he said shortly. Then, going up to Margherita, he went on in a low, forcible voice: 'I am coming with my coachman just now. She can't stay here; I can't do anything for her here. We will carry her out to the carriage and go home.' 'In this state?' she asked undecidedly. 'Do you want her to die here?' he interrupted brusquely. 'Please forgive me, sir.' He had already gone out, without his hat and overcoat, across the passage and icy court. After a minute he came back with the coachman, who had evidently got his orders. The doctor gently raised the fainting girl's body from under the arms, resting her head on his breast, while the coachman raised her feet. She was almost rigid and very heavy. The coachman had a frightened look; perhaps he thought he was carrying out a dead woman, all in black, through that bare parlour, deserted corridor, and chilly court; and although the sight of physical suffering was not new to him, being in a successful doctor's service, the idea of carrying a young woman's cold body, a corpse perhaps, gave him such a shudder he turned away his head. Old Margherita, coming behind, looked yellower, more like wrinkled parchment than ever, in the bright court. The procession of the anxious doctor, the frightened man, the rigid figure in black, and the old servant sadly bent by a strange new anguish, moved silently across the silent, tomb-like cloister, like a funeral. Gently, with the care needed not to waken a sleeping baby, the two men placed the poor lifeless creature in the
- 42. carriage, her head against the cushions and her feet on the opposite seat. She had not given a sign of life whilst she was being carried; the two lines deepened between Dr. Amati's eyebrows, lines showing a strong will and deep thought, but which gave him an absent- minded look. Margherita still gently tried to rearrange the girl's loosened tresses that had fallen down, but she did not manage it, her lean hands trembled so; she, too, had got into the broad landau; she gathered up her mistress's hair caressingly, and the doctor heard her mutter, 'My darling! my darling!' He had lowered the blue blinds against indiscreet eyes; the carriage went at a foot-pace; and in that bluish, misty shade the slow pace kept up the idea of a funeral still more. However, the carriage stopped at one point; after a little the coachman opened the door, and handed in to the doctor a hermetically sealed phial, which he held to the unconscious girl's nose. A sharp smell of ether at once spread through the carriage, which was still going very slowly. Bianca Maria never moved; after a little there was one sign of feeling: her closed eyelids got red, big tears burst out between the lashes and ran down her cheeks. The doctor did not take his eyes off her for a minute, keeping her hand in his. She went on weeping, still unconscious, without giving another sign of life: as if she still felt sorrow through her unconsciousness, as if through her loss of memory one bitter recollection still remained—only one. She did not recover consciousness. When they got to the Rossi Palace courtyard, hardly was the door opened when a murmuring noise broke out, gradually growing stronger, impossible to restrain. Beside the carriage door the porter's wife called out and screamed as if the girl was dead. All the windows looking into the courtyard, all the landing-place doors, had opened to see the poor, fainting, pale creature in black, with hair hanging down, taken out of the carriage. The doctor vainly tried to insist on silence, but the cry of surprise and compassion grew louder, rising in the heavy air.
- 43. On the first-floor landing-place Gelsomina, Agnesina Fragalà's nurse, came out, holding the pretty, healthy infant in her arms; the happy mother, Luisella Fragalà, came behind her, dressed to go out, with her bonnet on. But she lingered, leaning on the iron railing, smiling vaguely at her baby, and looking pityingly on the strange escort. She had felt rather tired and preoccupied for some time past, for she had been going every day to the Santo Spirito shop, from an instinct, a presentiment, that was stronger than her pride, tying up the parcels of sweets and cakes with her ring-covered, white hands. 'Poor thing! poor thing!' Luisella Fragalà muttered; her compassion had a deeper, acuter feeling in it than the other people's had. Raising the heavy yellow brocade curtains behind her double windows on the first-floor, Signora Parascandolo's bloodless face appeared—the rich usurer's wife who had lost all her children. She seldom went out; she stayed shut up in her gorgeous apartment, full of rich furniture now quite useless and dreary, as she never received anyone since her sons died; only she looked out of the window now and then in a silly kind of way that had grown on her. On seeing Bianca Maria carried up in that way, the poor woman, who took an interest in nothing usually, opened the window, and her voice was added to the rising tumult, crying in prayer and supplication, 'Jesus, Jesus, help us!' All Domenico Mayer's misanthropic family came out on the third-floor landing, leaving their three-roomed little flat that looked on to the Rossi Theatre. First came the father's long, peevish face, and, having just left some copying work brought home from the Finance Office, he had sleeves on to save his coat; then Donna Christina, the mother, who had got rid of the tooth-ache but had a stiff neck instead; next Amalia, with her staring eyes, thick nose and lips, and sulky look of a girl who has not yet got a husband; and Fofò, still afflicted by the hunger which his relations said was a mysterious illness. The whole family nearly threw themselves over the railings out of curiosity, and shrieked out in a chorus: 'Poor girl! poor girl!' A woman in a muslin cap and a man in a blue sweeping-apron were at the window—even the
- 44. doctor's housekeeper; nor did they stop gazing when their master came up, so overpowering was the excitement in all the Rossi Palace. That carrying up the stair, amid the noisy compassion of all these different people, the frightened, pitying shrieks, that had a false ring about them, seemed endless to Dr. Amati; as for old Margherita, she shook with annoyance and shame, as if that noise and publicity were insulting to her mistress. When the door was shut behind them, she asked Giovanni in a fright: 'Is milord not in? Milady is ill.' 'No,' he said, making way for the bearers. Margherita shook her head despairingly. She went with the doctor and his man into Bianca Maria's room; the girl was laid on the bed. The man-servant went away. The doctor again tried to bring her back with ether—no result. He bit his lip; he said twice or thrice, 'It is impossible!' Once again he raised the violet eyelids, looking at her eyes. She was alive, but she did not recover consciousness. 'Where is her father?' he asked, without turning round. 'I don't know,' the old woman muttered. 'There will be some place he goes every day; send for him.' 'I will send, as you order me to,' she said, still hesitating; and she went out. He sat down by the bedside, and laid down the ether bottle, convinced now it was useless. That bare, cold little room, with a look of childish purity, had calmed somewhat the scientist's dull anger at not being able to cure nor find out the reason of the illness. He had seen, a hundred times, long, queer fainting fits; but they were from nervous illnesses, from abnormal temperaments, out of order from the beginning, and ordinary methods had overcome them. The colourless young girl seemed to be sleeping heavily, and she might remain so for many hours, wrapped up in the dark regions of unconsciousness. He armed himself with patience, turning over in
- 45. his mind medical books that spoke of such fainting fits. Twice or thrice Margherita had come back into the room, questioning him with an agonized look; he shook his head, 'No.' Then he asked her for brandy. She stood hesitating; there was none in the house. Amati told her to go and ask for it in his flat next door. With a teaspoon, a wretched one that had lost its plating, he opened the girl's lips, and poured the strong liquor through her closed teeth, with no result. Again, he asked Margherita, who was fidgeting about, to heat flannel cloths; seeing her still embarrassed, he told her to go to his house, and ask the housekeeper for some. Whilst she was away, Giovanni came back out of breath; he panted as he spoke. 'I have not found the Marquis anywhere, not at Don Crescenzio's lottery stand, nor at the Santo Spirito assembly, nor in Don Pasqualino the medium's house, where they meet every day.' 'Who meet?' asked the doctor distractedly, hardly listening to what he said. 'The Marquis's friends.... But I left word wherever he is to come back to the house, because her ladyship is ill.' 'Very good; send out this prescription,' said the doctor, who as usual wrote it with a pencil on a leaf from his pocket-book. The old servant's pale face looked disturbed. The doctor, always taken up about his patient, did not notice him. 'Go, and get it,' he said, feeling Giovanni was still there. 'It is because ...' the poor man stammered out. Then the doctor, just as he had done for Annarella, the glove-cutter's wretched wife, pulled ten francs out of his purse and gave them to him. '... the master not being in and not being able to tell the mistress,' Giovanni muttered, wishing to account for the want of money. 'Very good—all right,' said the doctor, turning to his patient.
- 46. But a loud ring at the bell sounded all through the flat. A resounding step was heard, and the Marquis di Formosa came in. He seemed only to see his daughter stretched out on the bed. He began kissing her hand and forehead, speaking loudly in great anguish. 'My daughter, my daughter, what is the matter with you? Answer your father. Bianca, Bianca, answer! Where have you the pain? how did it come? My darling, my heart's blood, my crown, answer me! It is your father calling you. Listen, listen, tell me what it is! I will cure you, dear, dear daughter!' And he went on exclaiming, crying out, sobbing, pale and red in the face, by turns, running his fingers through his white hair, his still graceful, strong figure bent, while the doctor looked at him keenly. In a silent interval the Marquis noticed Amati's presence, and recognised him as his celebrated neighbour. 'Oh, doctor,' he called out, 'give her something—this daughter is all I have!' 'I am trying what I can,' the doctor said slowly, in a low voice, as if he was chafing against the powerlessness of his science. 'But it is an obstinate faint.' 'Has she had it long?' 'About two hours. It came on in the Sacramentiste parlour.' 'Ah!' said the father, getting pale. The doctor looked at him. They said no more. The secret rose up between them, wrapped in the thickest, deepest obscurity. 'Do something for her,' Formosa stammered, in a trembling voice. But he was summoned; Giovanni whispered to him; the Marquis was undecided for a minute. 'I will come back at once,' he said as he went off. The doctor had wrapped the invalid's little feet in warm clothes; now he wanted to wrap up her hands. All at once he felt a slight pressure
- 47. on his hand: Bianca Maria with open eyes was quietly looking at him. The doctor's forehead wrinkled a little with surprise just for a moment. 'How do you feel?' he asked, leaning over the invalid. She gave a tired little smile, and waved her hand as if to tell him to wait, that she could not speak yet. 'All right, very good,' the doctor said heartily. 'Don't speak;' and he made Margherita, who was coming in, keep silence, too. The servant's poor tired eyes shone with joy when she saw Bianca Maria smiling. 'Are you better? Make a sign,' the doctor asked tenderly. She made an effort, and very low, instead of a sign, she pronounced the word 'Better.' The voice was low, but quiet. With a medical man's familiarity, he took one of her hands in his to warm it. 'Thank you!' said she after a time. 'For what?' he said, rather put out. 'For everything,' she replied, smiling again. Now, it seemed, she had quite got back the power of speaking. She spoke, but kept quite still, only living intensely in her eyes and smile. 'For everything—what do you mean?' he asked, piqued by a lively curiosity. 'I understood,' said she, with a profound look. 'You were conscious all the time?' 'All. I could neither move nor speak, but I understood.' 'Ah!' said he thoughtfully. He sent Margherita to let the Marquis know that his daughter had recovered consciousness. 'Were you in pain?'
- 48. 'Yes, a great deal, from not being able to come out of my faint. I wept; I felt a pain at my heart.' 'Yes, yes,' he said. 'Don't speak any more—rest.' The doctor made a sign to the Marquis, who was coming in, to keep silence. Formosa leant over his daughter's bed and touched her forehead with his hand, as if he was blessing her. Her eyelids fluttered and she smiled. 'Your daughter was conscious during her swoon—the rarest kind of fainting fit.' 'Was she conscious?' the Marquis asked in a strange voice. 'Yes; she saw and heard everything. It comes from sensitiveness carried to excess.' Then he poured out more brandy in the teaspoon for Bianca Maria to take. Don Carlo Cavalcanti's face twitched. He leant over the bed, and asked: 'What did you see? Tell me—what did you see?' The daughter did not answer. She looked at her father in such sad surprise that the doctor, turning round, noticed it and frowned. He had not heard what the father asked his daughter, and he again felt the great family secret coming up, seeing Bianca Maria's gentle, sad glance. 'Don't ask her anything,' the doctor said brusquely to the Marquis di Formosa. The old patrician restrained a disdainful shrug. He brooded over his daughter's face, as if he wanted to get the secret out by magnetism. She lowered her eyelids, but suffering was in her face; then she looked at the doctor, as if she wanted help. 'Do you want anything?' he asked. 'There is a man at my door: make him go away,' she whispered in a frightened tone.
- 49. The doctor started; so did her father. In fact, outside the door, in his invariable wretched waiting attitude, was Pasqualino De Feo, dirty, ragged, with unkempt beard and pale, streaky red cheeks. The Marquis had left him in the drawing-room, but he slid along to Bianca Maria's room with the timid, quiet step of a beggar who fears to be chased from all doors. 'Who is that man?' said the doctor in that rough tone of his, going up to the door, as if to chase him away. 'He is a friend,' the Marquis answered, hurrying forward in a vague, embarrassed way. 'Send him away!' the doctor said sternly. Outside the door the Marquis and Don Pasqualino chattered in a lively whisper. Bianca Maria looked as if she could hear what her father said outside; at one point she shook her head. 'Do you want that man sent away from the house?' 'Leave him,' she said feebly. 'It would annoy my father.' Ah! the doctor knew nothing at all. Even now, on coming back to stern realities, he blamed himself for the sad, dark romance coming into his life; but an overmastering feeling entangled him, which he thought was scientific curiosity. Hours were passing, evening was coming on; he had made none of his visits, and he stayed on in that poor aristocratic sick lady's room, as if he could not tear himself away. 'I ought to go,' he said, as if to himself. 'But you will come back?' she asked in a whisper. 'Yes ...' he said, determined to conquer himself and not come back again. 'Do come back!' in a humble voice, beseechingly. 'I am here—just next door. If you are in pain, send for me.' 'Yes, yes,' she replied, quieted at the idea of being protected.
- 50. 'Adieu, madame!' 'À Dieu!' she said, pointedly separating the two words. Margherita went with him, thanking him softly for having saved her mistress; but he had again become an energetic, busy man, inimical to words. 'Where is the Marquis?' he insisted on knowing. 'In the drawing-room, Professor.' And she took him there. It was just so. Don Carlo Cavalcanti, Marquis di Formosa, and Pasqualino De Feo were walking up and down silently. It was almost dark: still, the doctor examined the medium with a scrutinizing, suspicious eye. 'How is Bianca Maria?' asked Formosa, coming out of a dream. 'Better now,' the doctor replied in a short, cold tone; 'but she has been struck prematurely, owing to a growing want of balance, moral and physical. If you don't give her sun, movement, air, quiet, and cheerfulness, she may die—from one day to another.' 'Don't say so, doctor!' the father cried out, angry and grieved. 'I must tell you, because it is so. I don't know the reason of to-day's illness—I don't want to know it; but she is ill, you understand—ill! She needs sun and peace—peace and sun. If you want a doctor, I am always near; that is my profession. But I have made out a prescription. Send your daughter to the country. If she stays another year in this house, only seeing you and going to the nunnery, she will die, I assure you,' he persisted coldly, as if this truth ought to be announced decisively, as if he wanted to convince his own unwilling mind also. 'Doctor, doctor, do not say that!' Formosa moaned, asking for mercy. 'She is ill; she will die. To the country—the country! Good-evening, Marquis!'
- 51. He went off, as if trying to escape. The Marquis and the medium, who had not said a word, went on again with their silent walk. Now and then Formosa sighed deeply. 'The Spirit that helps me——' the medium breathed out. 'Eh?' the other cried out, starting. 'Warns me that Donna Bianca Maria has had a heavenly vision ... and that she will tell you it in an allegory.' 'What do you say? Is it possible? Has the Supreme Being granted me this favour? Is it possible?' 'The Spirit does not deceive,' the medium said sententiously. 'That is true—it is true!' Formosa murmured, looking into the darkness with wild eyes.
- 52. CHAPTER V CARNIVAL AT NAPLES From the first days of January, Naples was taken with a mania for work that spread from one house and shop to another, from street to street, quarter to quarter, from fashionable parts to the poorest, with a continuous movement, rising and falling. A stronger noise of saws, planes and hammers came from the factories and workshops: in the shops, with doors left ajar, and in the houses they sat up late: the smallest as well as the big industries seemed to have got a mysterious impulse, a breath of new life, into their half-dying state. The demand for gloves had increased beyond bounds, especially white and dove-coloured ones: the humblest general shops kept them. In the artificial-flower shops, that compete with the French trade with growing success, a great quantity of boughs, bunches, wreaths of flowers, and ferns were got ready; big and small bouquets of bright, warm-coloured flowers to take the eye—the finest intended for ladies' hair and bosoms, the coarser for decorating houses, shops, horses and carriages. Roses, camellias, pinks, were most in request. At all the tailors' and dressmakers', satin, velvet, gauze, crape, were draped in all styles, made into dresses, mantles, hoods, and scarves; whilst at the shoe-makers', binders spent ten hours a day making pink, blue, white, gray, and lilac shoes, fancy, gold-embroidered boots, and some bound in fur. The glove, flower, dress, and shoe makers' work began the first
- 53. hours in the morning and ended at eleven at night; but the only others that came up to them were the cardboard shops. Here paper, in men and women's hands, was bent into a thousand shapes and sizes. It was painted, cut out, twisted, even curled up; it was made up with straw, metal, and rich brocade stuff, starting from the twisted paper that holds a sweet or cracker to the big expensive box. From the little chocolate-box, made of cardboard and a scrap of satin, to the handsome, neat satchel with a second cardboard lining; from the roll, made of two or three old gambling cards, a little Bristol board, and bright-coloured pictures, to straw cornucopias, covered with ribbons; from ugly, mean things to lovely and expensive ones, the work was never-ending. All this paper-work was arranged on large boards; the colours were dazzling and took the eye. Every day they were sent off to the sweet-shops, where they were filled with confetti, dainties, sweets, and sugar almonds. Yes, the work was hardest, always, in the confectioners', from the humble Fragalà of San Lorenzo quarter and the gorgeous but middle-class Fragalà of Spirito Santo up to the exquisite fashionable confectioner in Piazza San Ferdinando. Above all, there was a grand making of caraways, white and coloured, of all sizes, with caraway- seeds and a powdery sugar covering; there were whole stores of them in tins, canisters of all sizes, overflowing baskets made like canisters, all kept carefully from damp, which ruins caraways. Such a stock!—if it had been gunpowder, there would have been enough to conquer an army. The other heavy work was getting sausages and black-puddings ready, all covered with yellow bits of Spanish bread— pig's blood, that is to say—made up with chocolate, pistachios, vanilla, lemon, and cinnamon, so presented as to hide the coarseness. In the back-shops they weighed cinnamon, sliced lemons, crushed pistachio nuts, boiled sweets of all colours and kinds; ovens roared, stoves were made red-hot, kettles boiled and gurgled, and workmen, in shirt-sleeves and caps, with bare arms and necks, stirring with big ladles, beating pestles in marble mortars, looked like odd figures in purgatory, lighted up by the furnace flames.
- 54. All trades were busy: advertisements were put up; whole sheets of them were spread on the city walls. Fashionable barbers took on new lads; the three celebrated Naples pizzaiuoli of Freddo and Chiaia Lanes, of Carità Square, of Port Alba, informed the public, which loves pizza with Marano and Procida wine, that they would be open till morning. The Café Napoli, the Grande, and the Europa covered their windows with thick cloths, and held a grand cleaning up all through the rooms; the theatres announced four times more illuminations, whilst at the door of fancy shops, the windows of miserable or fashionable bazaars, were shown black velvet masks, wax noses, and huge cardboard heads, three times the natural size, and much uglier than Nature; network masks, to protect the face from caraways, ladles for throwing them, long tongs for handing up sweets or flowers to the balconies, scarves and ribbons, fantastic ballroom decorations, and entire costumes of tissue-paper. Along the streets in Monte Calvario quarter, across and parallel to Toledo, in the darkest old-clothes shops and retail dealers', dominos hung on wooden pegs for the popular balls: Mephistopheles costumes in red and blue, Spanish grandees in cotton velvet, harlequins made up of old carpets, Sorrento peasant women's dresses in gay colours, Pulcinellos, and almost white dress; above all, shining helmets, with cuirass of cardboard to match, and wooden swords. Masquerading costumes were on hire everywhere for a few francs; they gave a jocular tone to these dull lanes, hanging even from the first-floor balconies, sticking out in a row from the damp, dark shops with grinning, devilish masks, or showing sickly faces of white or greeny- blue satin. Wherever one went, in lower class neighbourhoods as well as in aristocratic parts, one could see a lively movement, cheerful labour, a noisy bustling about, a never-ending activity, a daily and nightly ferment of all forces, the constant, lively, energetic action of a whole peaceful, laborious town, intent upon one single piece of work, given up to it heart and mind, hand and foot, using up its nerves, blood, and muscles in this one tremendous work. Everywhere, everywhere,
- 55. one guessed or knew it; it caught the eye; it was written up what this great work was—'For the coming carnival festivities.' Nothing else but the carnival. The great city gave itself over to that impetuous, joyous exertion, not for love of work in itself—for work that is the cause and consequence of well-doing, which in itself is the ground-work of goodness and respectability. The great town had not given itself over to that lively activity for any immediate civic reason, for hygienic improvements, industrial art exhibitions, changing old quarters or making new ones: it was for the carnival only—a carnival by official decree of the Prefecture and of the Municipal Palace; a carnival warmed up by committees, associations, commissions, set agoing by thousands of people, arranged and carried out as a great institution, widely spread in the minds of the whole five hundred thousand inhabitants, made to resound as far as the southern provinces, echoing even to Rome and to Florence, putting in the place of any other project, initiative or work, this of the carnival; nothing but the carnival—enthusiastically, even deliriously. But, as at the bottom of all joyous things in this land of Cockayne, there is an ever-flowing vein of bitterness. This carnival, that turned all the gravest persons and things in the town into fun and masquerade—this carnival was a merciful thing. From autumn to January the damp, grievous scirocco had blown in Naples' streets, overcoming the energies of healthy people, and making invalids' maladies worse. The winter crowd of foreigners was smaller than usual. Many works had been stopped for a time, and those just starting had been delayed, so that many poor people slept on the church steps under San Francesco di Paola portico and the Immacolata obelisk in Piazza Gesù. A great wind of fasting had blown with the scirocco, so that the official carnival, carried out by the desire of thousands, was intended, if it succeeded, to satisfy for ten days at least a lot of starving people, from shoe-binders to flower-makers, from tailors to shop-clerks, from wandering salesmen to the small shopkeepers. Twenty days' carnival!—that is to say, ten days' bread, and a relish with it. The idea had been taken up at
- 56. once. All helped, even the least enterprising, knowing they were putting out their money at good interest. Carnival, carnival, in the streets and balconies, in the gateways and houses! On that Shrovetide Thursday the damp winter scirocco had got a spring softness. Toledo Road, where the carnival spread from one end to the other, both in its popular and fashionable form, had put on an extraordinary appearance. All the big shops were shut. The tradesmen and their ladies wished to enjoy the day's outing, also they were nervous about their plate-glass windows. All the signs were covered with linen or tow, as were the gas-lamps. As to the common smaller shops, they had taken out the glass and put up wooden platforms, and the owners, with their friends and children, sat with a store of caraways, having to do battle almost face to face with the people on the pavement; but they bravely flourished their ladles all the same. The balconies on the first floor were all differently draped with bright, cheap muslins, put up with a few nails or pins, with a very Southern and rather barbarous love of gay colours, some in the style of church decorations, blue, red, white, and gold, some tucked back with big camellias, roses, and dahlias, to make the balcony look like an alcove, an actress's room, a saint's niche, or a wild beasts' show even. The finest and smartest hangings began near Santa Brigida. Some Swiss gentlemen had had a chalet put up in their balcony, and the ladies wore simple, rather silly costumes, with hair down, a big cap, and gold crosses at their necks. Just after that, at Santa Brigida, a great man's natural son had hung his balconies with dark-blue velvet, covered with a silver net, which might represent the firmament, the kingdom of the moon, or the sea, but, at any rate, it surprised the good Naples folk. A balcony near the Conte di Mola Lane was made into a kitchen, with a stove, kettle, frying and stew pans, and eight or ten youths of good family worked as cooks and scullions, with white caps and aprons. A famous beautiful woman, whose beauty brought her wealth and led her into deadly sin, had changed her balcony into a Japanese hut, all stuffs and tapestries. Now and then she appeared wrapped in flowing, soft robes, just gathered in at the waist, with her black hair
- 57. caught up in a shiny knot held by pins, her eyebrows arched in an unvarying look of surprise. The common people smiled admiringly as they passed. They said, with their vague one idea of the East, 'The Turk, the Turk!' All these balconies, draped from one end of the street to the other, and the shop decorations, began to make one dizzy with bright colours, firing the imagination, giving that quick feeling of voluptuous joy Southerners get from outside impressions. Towards eleven, wandering salesmen began to go about, shrieking out their wares. They sold little boxes of inferior sweets made in bright colours—red bags, green and white boxes, lilac and yellow horns, carried in big, flat baskets in one hand. They sold artificial flowers also, made into sprays, cockades, and bunches, tied on to long poles. Real flowers were sold, too—white camellias and perfumed violets, from big baskets; also masks, ladles, linen bags for caraways, red and yellow paper sunflowers, that twirled round at every breath of wind like wild things. They sold a bad quality of caraways, bought cheap, intended to be sold dear in the blind, furious time of the battle. At mid-day the traffic in sweetmeat-boxes, flowers, musks, and windmills began. Already the crowd began to fill the balconies and pavements, running up hurriedly from all the side-streets. On the first-floor windows and balconies a living, many-coloured hedge of women swayed about. There was a shimmer of girlish forms brightly dressed; their faces gently moved up and down like big pink and white flower-heads, with a blood-red touch now and then from an open parasol or scarlet hat. The balconies and windows of the second story were filled with still more excited people, whilst on the fourth children and girls here and there had thought of letting down a basket tied to a long bit of ribbon to fish with, smiling from above on some courteous unknown, who put a flower, some sweets, or a chocolate-box into the baskets of these smiling beings so near the sky. The people increased everywhere. Traffic with the hawkers went on from the balconies to the streets, with loud discussions, offers, and rejections, making the noise twice as great.
- 58. Caraways were not to be thrown before two o'clock, by the committee's express order, but some stray fights were started already. At San Sepolcro corner a peasant nurse, slowly swinging her petticoats, was fired at by some school-boys at close quarters. A grave gentleman, in top-hat and long great-coat, was violently assaulted in Carità Square. He tried to go at them with his stick, but he was hissed. Then he called for the police, announcing pompously he was Cavaliere Domenico Mayer, a State functionary; but the police would not help, saying it was carnival, and that he should not tempt people with his top-hat. And then the misanthropic Secretary of the Finance Department, full of bitterness, had gone into the San Liborio Lane to escape. A lady in a broad-brimmed hat, not able to move from one spot in the pavement near San Giacomo, had a continuous shower of caraways poured on her by a child on the third story. She heard it fall on her felt and feathers without daring to move or raise her head, in case she got the caraways in her face. At two o'clock exactly a cannon-shot was heard in the distance. Then there was a sigh of relief from one end of Toledo to the other, from the street to the upper stories, and the crowd swayed about. The four Rossi Palace balconies, first floor on the right, looking into Toledo, were draped in blue and white linen, caught back by big red camellias. Luisella Fragalà and her guests had thought of white and blue dominoes, with high, ridiculous hats and red cockades, and all the Naddeos, all the Durantes, all the Antonaccis, fat or thin, young or old, wore dominoes made in the house themselves to save their clothes from white powder, and, according to them, give an elegant look to the balcony. Some looked like big bundles, others like long ghosts; but the carnival madness had overcome these middle-class women. Besides all, trade was flourishing in these days. So many goods were sold; the men came back to the house in high good- humour, whilst all winter had been one complaint, and economy had got narrower and harder to bear. How happy they were, all these placid, industrious little women! In this time of carnival excitement they could share, in their blue and white fancy dresses and red cockades. Luisella Fragalà had thought out the costume, and that
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