sigmoid function

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.

Mathematical Model of Logistic Regression for Binary Classification. Part 1. Regression Models of Data Generalization

In this article, the mathematical justification of logistic regression as an effective and simple to implement method of machine learning is performed.

A review of literary sources was conducted in the direction of statistical processing, analysis and classification of data using the logistic regression method, which confirmed the popularity of this method in various subject areas.