Data Science Solutions with Python: Fast and Scalable Models Using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn

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

T. C. NokeriData Science Solutions with Pythonhttps://doi.org/10.1007/978-1-4842-7762-1_3

3. Linear Modeling with Scikit-Learn, PySpark, and H2O

Tshepo Chris Nokeri¹  

(1)

Pretoria, South Africa

 

This introductory chapter explains the ordinary least-squares method and executes it with the main Python frameworks (i.e., Scikit-Learn, Spark MLlib, and H2O). It begins by explaining the underlying concept behind the method.

Exploring the Ordinary Least-Squares Method

The ordinary least-squares method is used with data that has an output feature that is not confined (it’s continuous). This method expects normality and linearity, and there must be an absence of autocorrelation ...