Perbandingan Metode Cost Sensitive pada Decision Tree dan Naïve Bayes untuk Klasifikasi Data Multiclass

Perbandingan Metode Cost Sensitive pada Decision Tree dan Naïve Bayes untuk Klasifikasi Data Multiclass

Abstrak– Knowledge discovery is the method of extracting information from data in making informed decisions. Seeing as classifiers do have a lot of learning patterns in the data, testing an imbalanced dataset becomes a major classification issue. The cost-sensitive approach on the decision tree C4...

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Bibliographic Details
Main Authors: M Aldiki Febriantono, Sholeh Hadi Pramono, Rahmadwati Rahmadwati
Format: Article
Language:English
Published: Departement of Electrical Engineering, Faculty of Engineering, Universitas Brawijaya 2020-04-01
Series:Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems)
Subjects:
cost sensitive
decision tree
multiclass
naã¯ve bayes.
Online Access:https://jurnaleeccis.ub.ac.id/index.php/eeccis/article/view/625
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