Attribute Selection with Genetic Algorithm: Genetic Algorithm Based Attributes Subset Selection Using Naive Bays Classifier - Bhupendra Kumar,Somesh Kumar
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Piegāde 12-18 darba dienu laikā
30 dienu atgriešanas politika
Feature selection is the first task of any learning approach to define a relevant set of features. Several methods are proposed to deal with the problem of feature selection including filter, wrapper and embedded methods. In this work, we focus on feature subset selection to select a minimally sized subset of optimal features. Feature Selection is optimization problem; genetic algorithm based attribute subs ... Pilns apraksts
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Aprašymas
Feature selection is the first task of any learning approach to define a relevant set of features. Several methods are proposed to deal with the problem of feature selection including filter, wrapper and embedded methods. In this work, we focus on feature subset selection to select a minimally sized subset of optimal features. Feature Selection is optimization problem; genetic algorithm based attribute subset selection using naïve bayes classifier is used for this purpose. GABASS are found to be the best technique for selection purpose when there is very large population. The GABASS provides good results and their power lies in the good adaptation to the various and fast changing environments.
Vairāk informācijas
| Autors | Bhupendra Kumar, Somesh Kumar |
|---|---|
| Izdevējs | LAP Lambert Academic Publishing |
| Izlaides gads | 2016 |
| Vāka tips | Mīkstais vāks |
| EAN | 9783659871634 |