🌟 Day91 of #100DaysOfPython 🌟

Today, we're diving into Count/Frequency Encoding for handling categorical feature!

Count or frequency encoding is a method of encoding categorical variables by replacing each category with the count or frequency of occurrences in the dataset.

Instead of assigning arbitrary numerical values or creating multiple binary columns, count encoding simplifies the process by directly mapping categories to their occurrence counts or frequencies.

Advantages:

• This technique does not increase the feature space

Disadvantages:

• This technique does not provide differentiation to handle situations with same frequencies as it ends up providing same weights to the labels with same frequencies.

Stay tuned for more encoding technques!