Raman Microspectral Study and Classification of the Pathological Evolution of Breast Cancer Using Both Principal Component Analysis-Linear Discriminant Analysis and Principal Component Analysis-Support Vector Machine

Figure 8

Scattering plots of PCA-SVM algorithm based on three kernel functions. (a) PCA-SVM with linear kernel, (b) PCA-SVM with polynomial kernel, and (c) PCA-SVM with RBF kernel. Points in different colors represent different tissue types; background color represents class domain created by SVM (a, linear kernel; b, polynomial kernel; c, RBF kernel).

(a)

(b)

(c)