Wheat Production Analysis based on Naive Bayes Classifier

Jasmine Kaur ,Dr. Pankaj Bhambri, Kapil Sharma

Page No: 47-51

The most important culture being followed in India since ancient times is agriculture. The crops were cultivated by the people in ancient times within their own land areas such that they could fulfill their own requirements. India is a farming nation. Crop production analysis is one of the applications of prediction analysis. This study is related to paddy production. To improve 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 reduction in execution time. The performance of SVM, KNN and Naïve 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.

Citations

APA: Jasmine Kaur ,Dr. Pankaj Bhambri, Kapil Sharma (2025). Wheat Production Analysis based on Naive Bayes Classifier. DOI: 10.86493/OTJ.2433908

AMA: Jasmine Kaur ,Dr. Pankaj Bhambri, Kapil Sharma. Wheat Production Analysis based on Naive Bayes Classifier. 2025. DOI: 10.86493/OTJ.2433908

Chicago: Jasmine Kaur ,Dr. Pankaj Bhambri, Kapil Sharma. "Wheat Production Analysis based on Naive Bayes Classifier." Published 2025. DOI: 10.86493/OTJ.2433908

IEEE: Jasmine Kaur ,Dr. Pankaj Bhambri, Kapil Sharma, "Wheat Production Analysis based on Naive Bayes Classifier," 2025, DOI: 10.86493/OTJ.2433908

ISNAD: Jasmine Kaur ,Dr. Pankaj Bhambri, Kapil Sharma. "Wheat Production Analysis based on Naive Bayes Classifier." DOI: 10.86493/OTJ.2433908

MLA: Jasmine Kaur ,Dr. Pankaj Bhambri, Kapil Sharma. "Wheat Production Analysis based on Naive Bayes Classifier." 2025, DOI: 10.86493/OTJ.2433908