Learn and read the complete course of Logistic Regression Model For machine Learning step by step. This book is very important and useful. It is a statistical model. Logistic Regression Model is a basic form uses a logistic function which is used to model a binary dependent variable, although many more complex extensions exist. Its widely used in data describing and used to explain the relationships between one dependent binary variable and one or more nominal, interval independent variables. Logistic Regression Model is used as an equation which is used for the representation as like linear regression. Logistic Regression Model is very useful and beneficial in machine learning algorithms. In this book you will learn different different topics of Logistic Regression Model.
In this book we will learn detail of Important Special Cases of the Logistic Model.
- Detail of Computing the Odds Ratio in Logistic Regression.
- Presentation of Maximum likelihood techniques.
- Objectives of modeling strategy guidelines.
- Introduction of modeling strategy for assessing interaction and confounding.
- Presentation of additional modeling strategy issues.
- Detail of analysis of matched data using logistic regression.
- Explanation of polydomous logistic regression.
- Ordinal logistic regression.
- Approaches for analysis of correlated data in detail
- Datasets of Computer Programs for Logistic Regression.