The Effect of Feature Selection on Music Genre Classification
| Main Authors: | Giri, I Nyoman Yusha Tresnatama, Putri, Luh Arida Ayu Rahning |
|---|---|
| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University
, 2021
|
| Online Access: |
https://ojs.unud.ac.id/index.php/JLK/article/view/64437 https://ojs.unud.ac.id/index.php/JLK/article/view/64437/39699 |
Daftar Isi:
- One of the things that affects classification results is the correlation of features to the class of a data. This research was conducted to determine the effect of the reduction of features (independent variable) that have the weakest correlation or have a distant relationship with the class (dependent variable). Bivariate Pearson Correlation is used as a feature selection method and K-Nearest Neighbor is used as a classification method. Results of the test showing that, 75.1% average accuracy was obtained for classification without feature selection, while using feature selection, average accuracy was obtained in the range of 75% - 79.3%. The average accuracy obtained by the selection of features tends to be higher compared to the accuracy obtained without selection of features.