Improved Parametric and Nonparametric Classification Techniques

Language: English

Published by LAP LAMBERT Academic Publishing Sep 2020, 2020

6202917318 / 9786202917315

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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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This item is printed on demand - it takes 3-4 days longer - Neuware -This text considers different parametric and nonparametric classification techniques to classify objects, and make a comparative study among these techniques. In most of the situations, classification techniques give few misclassifications under large samples as well as under the normal populations. If the data set comes from the non-normal populations, then we apply Box-Cox transformation to transform this data set into near normal. Hence, we investigate the effect of Box-Cox transformation and see that Box-Cox transformed data generates better discrimination and classification techniques. Also if the sample size is small, then we use the Bootstrap approach for classifying objects, and investigate that the Bootstrap classification technique used in this analysis performs better than the usual techniques of small samples. There is no unique classification technique that is suitable for all the situations, also examines that nonparametric classification techniques perform better than the parametric classification techniques, whereas the Neural Network classification technique gives optimum solutions among the nonparametric classification techniques. 124 pp. Englisch.…

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Title
Improved Parametric and Nonparametric Classification Techniques
Author
Md. Mahabubur Rahman
Publisher
LAP LAMBERT Academic Publishing Sep 2020
Publication year
2020
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6202917318
ISBN 13
9786202917315
Item weight
203 grams
Dimensions
220x150x8 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

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BuchWeltWeit Ludwig Meier e.K.

Germany