Dimensionality reduction can be roughly grouped into feature selection and feature extraction methods. We already employed some kind of feature selection in almost every chapter when we invented, analyzed, and then probably dropped some features. In this chapter, we will present some ways that use statistical methods, namely correlation and mutual information, to be able to do so in vast feature spaces. Feature extraction tries to transform the original feature space into a lower-dimensional feature space. This is especially useful when we cannot get rid of features using selection methods, but still we have too many features for our learner. We will demonstrate this using principal component analysis (PCA), linear discriminant analysis (LDA), and multidimensional scaling (MDS).
Building Machine Learning Systems with Python - Second Edition
By :
Building Machine Learning Systems with Python - Second Edition
By:
Overview of this book
<p>Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python is a wonderful language to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation. With its excellent collection of open source machine learning libraries you can focus on the task at hand while being able to quickly try out many ideas.</p>
<p>This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and introducing libraries. You’ll quickly get to grips with serious, real-world projects on datasets, using modeling, creating recommendation systems. Later on, the book covers advanced topics such as topic modeling, basket analysis, and cloud computing. These will extend your abilities and enable you to create large complex systems.</p>
<p>With this book, you gain the tools and understanding required to build your own systems, tailored to solve your real-world data analysis problems.</p>
Related Content you might be interested in
Current Title:
Building Machine Learning Systems with Python - Second Edition
No titles found
Table of Contents (20 chapters)
Building Machine Learning Systems with Python Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Getting Started with Python Machine Learning
Classifying with Real-world Examples
Clustering – Finding Related Posts
Topic Modeling
Classification – Detecting Poor Answers
Classification II – Sentiment Analysis
Regression
Recommendations
Classification – Music Genre Classification
Dimensionality Reduction
Where to Learn More Machine Learning
Index
Customer Reviews