Reliability analysis of psoriasis decision support system in principal component analysis framework

The proposed system using principal component analysis shows the best classification accuracy of 99.39% for a 10-fold cross-validation using polynomial kernel of order-2 on a set of 540 images. We validate our system by computing the reliability and stability indices. The results demonstrate a mean reliability index of 98.71% for 11 distinct data sizes, and meeting the stability criteria within 2% tolerance. The ability to retain the dominant features by inclusion of increasing set of features is 90.52%. Thus proposed system shows the encouraging results with higher accuracy, reliability, stability and retaining power of dominant features.