Many machine learning algorithms and almost all deep learning architectures are incapable of processing plain texts in their raw form. This means that their input to the algorithms must be numerical ...

Hello! This page is just a short summary of what the repository contains. So far it contains a function which can be used for Likelihood encoding (aka Mean Encoding) for categorical variables. Mean ...

A categorical variable is a type of variable that can be divided into distinct groups or categories.

The handling of categorical variables is a major challenge while using Bayesian Optimization (BO). Recent publications address this problem by introducing novel BO-frameworks adjusted specifically for ...

Handling categorical features to preprocess before building machine learning models. Techniques of encoding categorical features to numeric.

Dr. James McCaffrey of Microsoft Research uses a full code program and screenshots to explain how to programmatically encode categorical data for use with a machine learning prediction model such as a ...

Categorical Encoding Methods A set of scikit-learn-style transformers for encoding categorical variables into numeric by means of different techniques.