Mathematical Model of Logistic Regression for Binary Classification. Part 2. Data Preparation, Learning and Testing Processes
This article reviews the theoretical aspects of logistic regression for binary data classification, including data preparation processes, training, testing, and model evaluation metrics.
Requirements for input data sets are formulated, methods of coding categorical data are described, methods of scaling input features are defined and substantiated.