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Klasifikasi dengan Analisis Komponen Utama Kernel
(2013)
Principal component analysis (PCA) is a special case of the kernel PCA with linear kernel function. The aim of this study is to resolve the data problem that is not linearly separated and to classify an object into a group ...
Klasifikasi dengan Analisis Diskriminan Fisher, Jarak Mahalanobis, dan Analisis Biplot
(2013)
The classification of a new object into a group is expected to be solved with minimum error. Fisher discriminant analysis, Mahalanobis distance (either with separate or pooled covariance matrix), and biplot analysis are ...