Design of Paddy Crop Production Technique: Using K-Mean, Naive Bayes, KNN and SVM Classifiers - Couverture souple

Bhambri, Pankaj

 
9786202683302: Design of Paddy Crop Production Technique: Using K-Mean, Naive Bayes, KNN and SVM Classifiers
Couverture souple
ISBN 10 : 6202683309 ISBN 13 : 9786202683302
Editeur : LAP LAMBERT Academic Publishing, 2020

Synopsis

Crop production analysis is one of the applications of prediction analysis. This study is related to paddy production. In the previous research work, the SVM and KNN algorithm is implemented to analyze prediction. To improve the accuracy of the paddy production, the hybrid classifier will be designed based on K-mean clustering and Naive Bayes classifier. The presented and earlier algorithms will be applied in python and it is expected that accuracy will be improved with a reduction in execution time. The performance of SVM, KNN, and Naive Bayes is compared for the wheat production prediction. Naive Bayes is the best classifier for the wheat production prediction as per the obtained analytic results.

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Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2020
Langue
anglais
ISBN 10 
6202683309
ISBN 13 
9786202683302
Reliure
Broché
Nombre de pages
76
Coordonnées du fabricant
non disponible
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