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Machine Learning Quick Reference
book

Machine Learning Quick Reference

by Rahul Kumar
January 2019
Intermediate to advanced content levelIntermediate to advanced
294 pages
6h 43m
English
Packt Publishing
Content preview from Machine Learning Quick Reference

Kernel PCA

The Kernel PCA is an algorithm that not only keeps the main spirit of PCA as it is, but goes a step further to make use of the kernel trick so that it is operational for non-linear data:

  1. Let's define the covariance matrix of the data in the feature space, which is the product of the mapping function and the transpose of the mapping function:

 

It is similar to the one we used for PCA.

  1. The next step is to solve the following equation so that we can compute principal components:

Here, CF is the covariance matrix of the data in feature ...

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Publisher Resources

ISBN: 9781788830577Supplemental Content