feature-engineering-kit

What problem does it solve?

This Skill automates the creation of new features for machine learning models, simplifying the process of preparing data for training.

Core Features & Use Cases

• Encodings: Handles categorical data with one-hot, label, and target encoding.
• Scaling: Normalizes numerical features using standard or min-max scaling.
• Transformations: Creates polynomial features, interaction terms, and bins continuous data.
• Use Case: Prepare a dataset for a classification task by encoding categorical columns, scaling numerical features, and generating interaction terms between relevant variables.

Quick Start

Run the feature engineering kit to encode categorical features, impute missing values with the mean, and scale numerical features using standard scaling on the 'train.csv' file, saving the output to 'engineered.csv'.