Disease Inference on Medical Datasets Using Machine Learning and Deep Learning Algorithms

Abstract

This paper discusses the implementation of deep learning algorithm to process the cancer dataset and identify the relevance of classification test data. Performance comparison is made with the existing classifiers. In the field of machine learning, deep learning is the emerging field that has gained a lot of interest over the past few years. It is a powerful machine learning tool that can be applied for many applications and complex problems, We have applied correlation coefficient based filter as dimensionality technique. Suitable classification algorithms like naive bayes, random forest, J48, bagging and decision stump are applied on the dimensionality reduced datasets. The same experiment is performed using deep learning algorithms. The results of classification of the proposed approaches using deep learning algorithms are compared with well-known classification algorithms. It is evident from the results that the deep learning algorithms perform better compared to other classification algorithms.