Book Image

Learning Data Mining with Python

Book Image

Learning Data Mining with Python

Overview of this book

Table of Contents (20 chapters)
Learning Data Mining with Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Chapter 2. Classifying with scikit-learn Estimators

The scikit-learn library is a collection of data mining algorithms, written in Python and using a common programming interface. This allows users to easily try different algorithms as well as utilize standard tools for doing effective testing and parameter searching. There are a large number of algorithms and utilities in scikit-learn.

In this chapter, we focus on setting up a good framework for running data mining procedures. This will be used in later chapters, which are all focused on applications and techniques to use in those situations.

The key concepts introduced in this chapter are as follows:

  • Estimators: This is to perform classification, clustering, and regression

  • Transformers: This is to perform preprocessing and data alterations

  • Pipelines: This is to put together your workflow into a replicable format