HIGHLIGHTS
- who: Dian Translation from the Department of Statistics, Akademi Statistika Muhammadiyah Semarang have published the paper: Comparative analysis of classification algorithms for critical land prediction in agricultural cultivation areas, in the Journal: (JOURNAL)
- what: In this study a comparison framework is proposed to determine the classification algorithms' performance namely C.45 ID3 Random Forest k-Nearest Neighbor and Naïve Bayes. With the motivation to seek an efficient approach for critical land prediction, the authors propose a new approach to classify critical land with data mining.
- how: In this study a statistical significance . . .
If you want to have access to all the content you need to log in!
Thanks :)
If you don't have an account, you can create one here.