Article | REF: H5012 V1

Unsupervised statistical machine learning

Author: Bruno SAUVALLE

Publication date: January 10, 2020, Review date: January 18, 2021

You do not have access to this resource.
Click here to request your free trial access!

Already subscribed? Log in!


Français

3. Dimensionality reduction

The diversity of algorithms used in dimensionality reduction is due first and foremost to the fact that the objectives of dimensionality reduction vary widely.

If we use this technique simply for visualization purposes, to understand the distribution of a data set, we'll naturally look for an algorithm that best preserves the local or global structure of the data, taking as a reference, for example, the respective distances between each example. If, on the other hand, such a dimensionality reduction is used to feed a classification algorithm, the algorithm will be asked to retain the most discriminating variables for the classification that follows.

3.1 Feature selection

Feature selection is the most direct method of reducing the dimensionality...

You do not have access to this resource.

Exclusive to subscribers. 97% yet to be discovered!

You do not have access to this resource.
Click here to request your free trial access!

Already subscribed? Log in!


The Ultimate Scientific and Technical Reference

A Comprehensive Knowledge Base, with over 1,200 authors and 100 scientific advisors
+ More than 10,000 articles and 1,000 how-to sheets, over 800 new or updated articles every year
From design to prototyping, right through to industrialization, the reference for securing the development of your industrial projects

This article is included in

Technological innovations

This offer includes:

Knowledge Base

Updated and enriched with articles validated by our scientific committees

Services

A set of exclusive tools to complement the resources

Practical Path

Operational and didactic, to guarantee the acquisition of transversal skills

Doc & Quiz

Interactive articles with quizzes, for constructive reading

Subscribe now!

Ongoing reading
Dimensionality reduction