PENGARUH FORWARD SELECTION PADA KLASIFIKASI MENGGUNAKAN ALGORITMA NAIVE BAYES

MUNADI, MISBAHUDIN and Yusliani, Novi and Rodiah, Desty (2019) PENGARUH FORWARD SELECTION PADA KLASIFIKASI MENGGUNAKAN ALGORITMA NAIVE BAYES. Undergraduate thesis, Sriwijaya University.

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Abstract

Naive Bayes is a classification method that has an independence assumption for classification, but in fact, independent assumptions on attributes almost never happen. Therefore, this study will examine the effect of forward selection, which is a forward selection method that depends on dependency of each attribute. Then the attribute model will be evaluation and compared with without the selection feature. Based on the evaluation results conducted produces effects using harmonic mean values of F Measure and accuracy on the naive bayes method, and the naive bayes method with forward selection on the Pima Indians Diabetes dataset of 0.7391, and 0.7538. In the Breast Cancer dataset of 0.7120, and 0.7120. And the SPECTF Heart dataset is 0.5453, and 0.5962. Forward selection with the collaboration between the dependent attributes to produce a simpler attribute model and shows that forward selection has the effect of optimizing the naïve bayes classification method, naïve bayes with forward selection can work with simpler attributes

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Classification , Naive Bayes, Forward Selection, Pearson Correlation.
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 3825 not found.
Date Deposited:	27 Dec 2019 07:26
Last Modified:	27 Dec 2019 07:26
URI:	http://repository.unsri.ac.id/id/eprint/22420

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