Dimensionality Reduction – Data Mining Fundamentals Part 14

Dimensionality reduction has a specific purpose for data preprocessing. When dimensionality increases, data becomes increasingly sparse in the space that it occupies. Dimensionality reduction will help you avoid this.

Part 15:
Feature Subset Selection

Part 13:
Types of Sampling

Complete Series:
Data Mining Fundamentals

More Data Science Material:
[Video] Event Log Mining with R
[Blog] Custom R Models in Azure Machine Learning


About The Author
- Data Science Dojo is a paradigm shift in data science learning. We enable all professionals (and students) to extract actionable insights from data.


You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>