Nonlinear Principal Component Analysis and Its Applications (SpringerBriefs in Statistics) by Yuichi Mori
English | 28 Dec. 2016 | ISBN: 981100157X | 90 Pages | PDF | 1.87 MB
This book expounds the principle and related applications of nonlinear principal component analysis (PCA), which is useful method to analyze mixed measurement levels data.
In the part dealing with the principle, after a brief introduction of ordinary PCA, a PCA for categorical data (nominal and ordinal) is introduced as nonlinear PCA, in which an optimal scaling technique is used to quantify the categorical variables. The alternating least squares (ALS) is the main algorithm in the method.