Distributed Machine Learning with PySpark: Migrating Effortlessly from Pandas and Scikit-Learn

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2023

A. TestasDistributed Machine Learning with PySparkhttps://doi.org/10.1007/978-1-4842-9751-3_7

7. Logistic Regression with Pandas, Scikit-Learn, and PySpark

Abdelaziz Testas¹  

(1)

Fremont, CA, USA

 

This chapter focuses on classification, a distinct form of supervised learning. Our objective is to build, train, and evaluate a logistic regression model and then use it to predict the likelihood of diabetes.

Despite its name suggesting a connection to linear regression, logistic regression is fundamentally distinct in its purpose and methodology. Contrary to linear regression, which predicts continuous numerical values (see Chapter 3), logistic regression predicts ...