Machine Learning

CatBoost

Gradient boosting designed to handle categorical features effectively.

CatBoost is a gradient-boosting framework that can process categorical variables without requiring extensive manual one-hot encoding. It uses specialised techniques to transform categories while reducing target leakage.

The framework often performs well with minimal preprocessing and provides strong default settings. It is useful for datasets containing many categorical columns, such as customer, product or transaction data.

Also in Machine Learning

Supervised Learning Unsupervised Learning K-Means K-Nearest Neighbours Logistic Regression Linear Regression

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