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Mori, Yuichi; Kuroda, Masahiro; Makino, Naomichi - Nonlinear Principal Component Analysis and its Applications - 9789811001574 - V9789811001574
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Nonlinear Principal Component Analysis and its Applications

€ 81.23
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Description for Nonlinear Principal Component Analysis and its Applications Paperback. Series: SpringerBriefs in Statistics. Num Pages: 80 pages, 9 black & white illustrations, 8 colour illustrations, biography. BIC Classification: PBT; UFM. Category: (G) General (US: Trade). Dimension: 235 x 155 x 5. Weight in Grams: 150.
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. Multiple correspondence analysis (MCA), a special case of nonlinear PCA, is also introduced. All formulations in these methods are integrated in the same manner as ... Read more

Product Details

Format
Paperback
Publication date
2016
Publisher
Springer Verlag, Singapore Singapore
Number of pages
80
Condition
New
Series
SpringerBriefs in Statistics
Number of Pages
80
Place of Publication
Singapore, Singapore
ISBN
9789811001574
SKU
V9789811001574
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About Mori, Yuichi; Kuroda, Masahiro; Makino, Naomichi
Yuichi Mori, Professor, Okayama University of Science Masahiro Kuroda Professor, Okayama University of Science

Reviews for Nonlinear Principal Component Analysis and its Applications
“This book endeavors to demonstrate the usefulness of theory and applications of the nonlinear PCA and MCA. The authors have written an interesting and high valuable book, which gives an excellent overview to the mathematical foundations and the statistical principles of its themes. At the end of each chapter, a short list of references is provided and this will help ... Read more

Goodreads reviews for Nonlinear Principal Component Analysis and its Applications


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