Book Image

Learning Data Mining with Python - Second Edition

By : Robert Layton
Book Image

Learning Data Mining with Python - Second Edition

By: Robert Layton

Overview of this book

This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now. With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Feature selection


After initial modeling, we will often have a large number of features to choose from, but we wish to select only a small subset. There are many possible reasons for this:

  • Reducing complexity: Many data mining algorithms need significantly more time and resources when the number of features increase. Reducing the number of features is a great way to make an algorithm run faster or with fewer resources.
  • Reducing noise: Adding extra features doesn't always lead to better performance. Extra features may confuse the algorithm, finding correlations and patterns in training data that do not have any actual meaning. This is common in both smaller and larger datasets. Choosing only appropriate features is a good way to reduce the chance of random correlations that have no real meaning.
  • Creating readable models: While many data mining algorithms will happily compute an answer for models with thousands of features, the results may be difficult to interpret for a human. In these cases...