2021 : Ekstraksi Fitur menggunakan Kernel PCA pada SVM untuk Klasifikasi pada Data Microarray

Dr. Santi Wulan Purnami S.Si., M.Si

Year

2021

Published in

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External link

Type

RESEARCH

Keywords

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Abstract

Microarray analysis is becoming a powerful technique for clinical diagnosis, as they have the probable to discover gene expression patterns. This problem has received increased attention in statistics field and cancer research. Microarray data is high-dimensional data that consists of tens to thousands of features. The problems encountered in high-dimensional is many of insignificant and irrelevant features that tend to lose useful information and processing data inefficient. Therefore dimension reduction through feature extraction is an important thing to do before classification analysis