Visualization of Iris Data Using Principal Component Analysis and Kernel Principal Component Analysis
Principal component analysis (PCA) is a method used to reduce dimentionality of the dataset. However, the use of PCA failed to carry out the problem of non-linear and non-separable data. To overcome this problem such data is more appropriate to use PCA method with the kernel function, which is known...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Fakultas MIPA Universitas Jember
2010-01-01
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| Series: | Jurnal Ilmu Dasar |
| Subjects: | |
| Online Access: | https://jurnal.unej.ac.id/index.php/JID/article/view/104 |