COMPARATIVE STUDY OF SVM AND CNN IN IDENTIFYING THE TYPES OF SKIN CANCER

The objective of the paper is to analyze the performance of the machine learning algorithms in detecting the types of skin cancer. There are different types of skin cancer and some of them may lead to death. So, the early prediction of skin cancer helps in reducing the death rate. The dataset is downloaded from Kaggle website. The train data consists of 2637 images of benign and malignant images and the test data consists of 660 images of benign and malignant images. The aim of the paper is to identify the algorithm, which gives maximum accuracy in detecting the types of skin cancer when applied on the image dataset. The algorithms used are Convolution Neural Network (CNN) and Support Vector Machine (SVM). The algorithms are executed using Tensor Flow in Python.