Accurate Detection and Classification of Melanoma Skin Cancer Using Decision Tree Algorithm over CNN

The study’s primary purpose is to propose an automatic melanoma cancer detection system using the Decision Tree algorithm and convolutional neural network detect compare their accuracy. Group 1 was with a sample size of 10, 2 10. They were iterated 20 times predict accuracy percentage identifying cancer. Compared accuracy(75.58 %), method has substantially higher (85.61%). p=0.018 (p<0.05) Independent Sample T-test high statistical significance. Within scope this study, outperforms networks in skin detection.