Comparative Analysis of Machine Learning and Deep Learning Algorithms for Skin Cancer Detection

Abstract

Skin cancer is a typical type of disease, and early recognition builds the endurance rate. Skin cancer is a perilous and far and wide sickness. The endurance rate is under 14% whenever analyzed in later stages. Notwithstanding, if skin cancer is recognized at the beginning phases, the endurance rate is almost 97%. This requests the early location of skin cancer. Motivated by the same we, in this research we implemented different machine learning and deep learning techniques for skin cancer detection. We performed the comparative analysis of various machine and deep learning models, implemented on a fixed dataset. The analysis was based on accuracy and it was observed that the deep learning techniques produced enhanced results. The various techniques we used in this paper are, CNN, RESNET, DECISION TREE, KNN, SVM, NAÏVE BAYERS, INCEPTION V3, VGG -16. Accuracy was used as the performance measure.