Fractional Fourier transform information utilized as features
Mammogram
200
They selected ROI for avoiding redundant complexity. When SVM and Principal Component Analysis were used together the achieved Accuracy, Sensitivity and Specificity are %, % and % respectively.
ROI extracted for reducing redundant complexity. SVM and Mixed Gravitational Search Algorithm (MGSA) used together for feature reduction. The achieved Accuracy 86.00%; however SVM with MGSA method achieved 93.10% Accuracy.