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New Theory of Discriminant Analysis After R. Fisher
Shuichi Shinmura
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Description for New Theory of Discriminant Analysis After R. Fisher
Hardback. Num Pages: 208 pages, 3 black & white illustrations, 25 colour illustrations, 26 colour tables, biography. BIC Classification: JHBC; PBT; PSA. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 14. Weight in Grams: 508.
This is the first book to compare eight LDFs by different types of datasets, such as Fisher’s iris data, medical data with collinearities, Swiss banknote data that is a linearly separable data (LSD), student pass/fail determination using student attributes, 18 pass/fail determinations using exam scores, Japanese automobile data, and six microarray datasets (the datasets) that are LSD. We developed the 100-fold cross-validation for the small sample method (Method 1) instead of the LOO method. We proposed a simple model selection procedure to choose the best model having minimum M2 and Revised IP-OLDF based on MNM criterion was found to be ... Read more
This is the first book to compare eight LDFs by different types of datasets, such as Fisher’s iris data, medical data with collinearities, Swiss banknote data that is a linearly separable data (LSD), student pass/fail determination using student attributes, 18 pass/fail determinations using exam scores, Japanese automobile data, and six microarray datasets (the datasets) that are LSD. We developed the 100-fold cross-validation for the small sample method (Method 1) instead of the LOO method. We proposed a simple model selection procedure to choose the best model having minimum M2 and Revised IP-OLDF based on MNM criterion was found to be ... Read more
Product Details
Format
Hardback
Publication date
2017
Publisher
Springer Verlag, Singapore Singapore
Number of pages
208
Condition
New
Number of Pages
208
Place of Publication
Singapore, Singapore
ISBN
9789811021633
SKU
V9789811021633
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Shuichi Shinmura
Shuichi Shinmura, Seikei University
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