Classification of skin cancer using artificial neural network classifier in comparison with support vector machine classifier

Machine Learning techniques employed to predict classification of novel Skin Cancer detection using Support Vector Machine in comparison with Artificial Neural Network Classifiers. Classification of novel skin cancer detection is performed by Artificial Neural Network whereas number of samples (N=10) and Support Vector Machine Classifier where number of samples (N=10) techniques with pretest value 80 %. The accuracy rate of Artificial Neural Network is 98.32 % whereas results of Support Vector Machine accuracy rate is 86.17 %. The Sensitivity rate is 98.48 % for Artificial Neural Network whereas the results of Support Vector Machine sensitivity rate is 88.46 %. The Specificity rate is 96.12 % for Artificial Neural Network whereas results of Support Vector Machine have Specificity is 87.25 %. There is a significant difference in Accuracy rate (P < 0.05). Artificial Neural Network Classifier performs significantly better in finding the accuracy, sensitivity and specificity for predicting the classification of s kin cancer when compared to Support Vector Machine Classifier