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_8

8. Cluster Analysis with Scikit-Learn, PySpark, and H2O

Tshepo Chris Nokeri¹  

(1)

Pretoria, South Africa

 

This chapter explains the k-means cluster method by implementing a diverse set of Python frameworks (i.e., Scikit-Learn, PySpark, and H2O). To begin, it clarifies how the method apportions values to clusters.

Exploring the K-Means Method

The k-means method is the most common distance-computing method. It is part of the unsupervised machine learning family. It employs the Euclidean distance objective function to efficiently compute the distance between values, then determines ...