July 2025
Beginner to intermediate
448 pages
15h 1m
English
Content preview from Statistics Every Programmer Needs
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5 Fitting a logistic regression
This chapter covers
- Model fitting
- Model interpretation and evaluation
- Classification metrics
- Data exploration through histograms and correlation heat maps
Logistic regression is a supervised learning method for predicting a binary response from one or more independent variables. It’s commonly used for classification tasks where the dependent variable represents two possible categories or classes (e.g., pass or fail, presence or absence). It estimates the probability that a given instance belongs to a particular category based on the values of the independent variables, or predictors, using the logistic function (also known as the sigmoid function) that maps the output to a range between 0 and 1. We’ll see ...
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