performs a 2D principal component analysis (PCA) and visualizes it.
PCAScatterPlot(Samples, Color, Marker)
matrix that includes sample vectors as rows
string that specifies marker color, can be 'r' (red), 'y' (yellow), 'g' (green), 'c' (cyan), 'b' (blue), 'm' (magenta) or 'k' (black)
string that specifies the character used as marker, can be '.' (point), 'o' (circle), '+' (plus), '*' (asterisk) or 'x' (cross)
This function applies a 2D principal component analysis (PCA) to the rows of Samples. All samples are projected to the plane spanned by the 1st and 2nd principal components.
Harald Galda, 'Development of a segmentation method for dermoscopic images based on color clustering', Kobe University, August 2003