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What is Feature Normalisation and Reduction Techniques about?

This document discusses feature level processing techniques for machine learning models. It describes feature normalization methods like min-max scaling and z-scoring to standardize feature values. It also explains feature reduction using principal component analysis (PCA) to reduce the number of features by identifying correlated features and retaining only the principal components. The document discusses limitations of PCA and the need for output transformation of categorical variables using techniques li

Author

Paulo Santos

Language

EN