Machine Learning with PySpark: With Natural Language Processing and Recommender Systems

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022

P. SinghMachine Learning with PySparkhttps://doi.org/10.1007/978-1-4842-7777-5_5

5. Logistic Regression

Pramod Singh¹  

(1)

Bangalore, Karnataka, India

 

This chapter focuses on building a logistic regression model with Pyspark along with understanding the ideas behind logistic regression. Logistic regression is used for classification problems. We have already seen classification details in earlier chapters. Although it is used for classification, still it’s called logistic regression. It is due to the fact that under the hood, linear regression equations still operate to find the relationship between input variables and target variables. The main distinction ...