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37. Predicting access to healthful food retailers with machine learning. (2021). McCluskey, Jill ; Amin, Modhurima ; Badruddoza, Syed.
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38. Mixed random forest, cointegration, and forecasting gasoline prices. (2021). Escribano, Alvaro ; Wang, Dandan.
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39. A random forest based approach for predicting spreads in the primary catastrophe bond market. (2021). Chen, Yining ; Barrieu, Pauline ; Makariou, Despoina.
    In: Insurance: Mathematics and Economics.
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40. Behaviour associated with the presence of a school sports ground: Visual information for policy makers. (2021). Vala, Roman ; Drazdilova, Pavla ; Kromer, Pavel ; Valova, Marie ; Platos, Jan.
    In: Children and Youth Services Review.
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41. Policy Evaluation of Waste Pricing Programs Using Heterogeneous Causal Effect Estimation. (2021). Valente, Marica.
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42. The Effect of Sport in Online Dating: Evidence from Causal Machine Learning. (2021). Lechner, Michael ; Okasa, Gabriel ; Boller, Daniel.
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43. Predicting Food Crises. (2020). Andree, Bo ; Spencer, Phoebe Girouard ; Wang, Dieter ; Johannes, Bo Pieter ; Chamorro, Andres Fernando ; Kraay, Aart C.
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44. The role of traditional discounted cash flows in the tragedy of the horizon: another inconvenient truth. (2020). Cifuentes, Arturo ; Baroud, H ; Vahedifard, F ; Espinoza, D ; Gentzoglanis, A ; Bisogno, M ; Luccioni, L ; Rojo, J ; Morris, J.
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45. Heterogeneous Treatment Effects of Nudge and Rebate:Causal Machine Learning in a Field Experiment on Electricity Conservation. (2020). Murakami, Kayo ; Ushifusa, Yoshiaki ; Ida, Takanori ; Shimada, Hideki.
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46. The Role of Education in Increasing Awareness and Reducing Impact of Natural Hazards. (2020). Mander, Ulo ; Aunap, Raivo ; Scott, Michael ; Holbrook, Jack ; Parn, Jaan ; Cerulli, David ; Kull, Ain.
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47. Forecasting Spare Parts Demand of Military Aircraft: Comparisons of Data Mining Techniques and Managerial Features from the Case of South Korea. (2020). Suh, Jong Hwan ; Choi, Boram.
    In: Sustainability.
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48. Comparative Performance of Machine Learning Algorithms in the Prediction of Indoor Daylight Illuminances. (2020). Ngarambe, Jack ; Kim, Gon ; Yun, Geun Young ; Irakoze, Amina.
    In: Sustainability.
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49. Exploring the Space of Possibilities in Cascading Disasters with Catastrophe Dynamics. (2020). Wang, Ziqi ; Mignan, Arnaud.
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50. Analysis of Necessary Support in the 2011 Great East Japan Earthquake Disaster Area. (2020). Tsuboyama-Kasaoka, Nobuyo ; Harada, Moeka ; Ishikawa-Takata, Kazuko.
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51. Application of Gated Recurrent Unit (GRU) Neural Network for Smart Batch Production Prediction. (2020). Li, Xuechen ; Ma, Xinfang ; Zhang, Shicheng ; Xiao, Fengchao ; Wang, Fei.
    In: Energies.
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52. Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship. (2020). Du, Yuquan ; Wang, Shuaian ; Yan, Ran.
    In: Transportation Research Part E: Logistics and Transportation Review.
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53. A semi-“smart predict then optimize” (semi-SPO) method for efficient ship inspection. (2020). Wang, Shuaian ; Yan, Ran ; Fagerholt, Kjetil.
    In: Transportation Research Part B: Methodological.
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54. Sparsity in optimal randomized classification trees. (2020). Blanquero, Rafael ; Carrizosa, Emilio ; Morales, Dolores Romero ; Molero-Rio, Cristina.
    In: European Journal of Operational Research.
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55. Separating the signal from the noise – Financial machine learning for Twitter. (2020). Fischer, Thomas G ; Schnaubelt, Matthias ; Krauss, Christopher.
    In: Journal of Economic Dynamics and Control.
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56. Ensemble Learning with Statistical and Structural Models. (2020). Mao, Jiaming ; Xu, Jingzhi.
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57. Targeting predictors in random forest regression. (2020). Christensen, Bent Jesper ; Borup, Daniel ; Muhlbach, Nicolaj Norgaard ; Nielsen, Mikkel Slot.
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58. Targeting predictors in random forest regression. (2020). Christensen, Bent Jesper ; Borup, Daniel ; Muhlbach, Nicolaj N ; Nielsen, Mikkel S.
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59. Assessing the Importance of an Attribute in a Demand SystemStructural Model versus Machine Learning. (2019). McCluskey, Jill ; Amin, Modhurima ; Badruddoza, Syed.
    In: Working Papers.
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60. Public Procurement Announcements in Spain: Regulations, Data Analysis, and Award Price Estimator Using Machine Learning. (2019). Montequin, Vicente Rodriguez ; Garcia, Manuel J ; Villanueva, Joaquin M ; Fernandez, Francisco Ortega.
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61. The Mechanism of Social Organization Participation in Natural Hazards Emergency Relief: A Case Study Based on the Social Network Analysis. (2019). Chen, Yingxin ; Tadikamalla, Pandu R ; Zhou, Lei ; Zhang, Jing.
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62. Separating the signal from the noise - financial machine learning for Twitter. (2018). Schnaubelt, Matthias ; Krauss, Christopher ; Fischer, Thomas G.
    In: FAU Discussion Papers in Economics.
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63. Predicting Match Outcomes in Football by an Ordered Forest Estimator. (2018). Lechner, Michael ; Knaus, Michael ; Goller, Daniel ; Okasa, Gabriel.
    In: Economics Working Paper Series.
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64. Optimal functional supervised classification with separation condition. (2018). GADAT, Sébastien ; Gerchinovitz, Sebastien ; Marteau, Clement.
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65. Classifying Firms with Text Mining. (2018). Caterini, Giacomo.
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66. Performance assessment of five MCP models proposed for the estimation of long-term wind turbine power outputs at a target site using three machine learning techniques. (2018). Diaz, Santiago ; Matias, Jose M ; Carta, Jose A.
    In: Applied Energy.
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67. Generalized Random Forests. (2018). Athey, Susan ; Wager, Stefan ; Tibshirani, Julie.
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68. Model economic phenomena with CART and Random Forest algorithms. (2017). David, Benjamin.
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69. Comments on: A random forest guided tour. (2016). Arlot, Sylvain ; Genuer, Robin.
    In: TEST: An Official Journal of the Spanish Society of Statistics and Operations Research.
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