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Hands-On Automated Machine Learning
book

Hands-On Automated Machine Learning

by Sibanjan Das, Umit Mert Cakmak
April 2018
Beginner to intermediate content levelBeginner to intermediate
282 pages
6h 52m
English
Packt Publishing
Content preview from Hands-On Automated Machine Learning

Principal Component Analysis

Principal Component Analysis (PCA) transforms the data in the high-dimensional space to a space of fewer dimensions. Let's consider visualization of a 100-dimensional dataset. It is barely possible to efficiently show the shape of such high-dimensional data distribution. PCA provides an efficient way to reduce the dimensionality by forming various principal components that explain the variability of the data in a reduced dimensional space.

Mathematically, given a set of variables, X1, X2,...., Xp, where there are p original variables. In PCA we are looking for a set of new variables, Z1, Z2,....,Zp, that are weighted averages of the original variables (after subtracting their mean):

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Publisher Resources

ISBN: 9781788629898Supplemental Content