An Innovative Analysis of Predicting Melanoma Skin Cancer Using CNN and Random Forest Algorithm

The study’s primary purpose is to propose an automatic melanoma cancer detection system using Random Forest Algorithm and Convolutional Neural Network algorithm (CNN) detect compare their accuracy. Group 1 was architecture with a sample size of 10, 2 10. They were iterated 20 times predict the accuracy percentage identifying cancer. Compared accuracy, method substantially more accurate (98%) (65%). random forest technique has statistical significance p=0.0018 (p<0.05). Independent Sample T-test high level importance. In context this investigation, outperforms in skin detection.