A Comparative Analysis of various Machine Learning and Deep Learning Models for Gene Expression

Abstract

A vast number of people are affected by cancer. It is a scary disease that requires timely detection and treatment. There are numerous ways through which it can be predicted. One such way is using gene expression. With the help of the genes, it can be found that a person is going to suffer from disease or not. In the literature, there are varieties of ML and DL methods that may be used to train and test computers on diverse datasets. This paper will provide an overview of various ML and DL models, as well as an evaluation of their performance on a specific dataset. Preprocessing of the data is done and then machines are trained and tested using various DL and ML models. Then the accuracy of the models is calculated. Lastly, the models are compared to find which model of ML and DL performs better for the given dataset.