Lung Cancer Stage Prediction Using Multi-Layer Perceptron and Deep Learning Classifier

Providing accurate diagnosis for cancer is a challenging problem in precision oncology. Multiomics Data about cancer cells comprises of details about cancer cells like their radius, texture, perimeter, area, smoothness, compactness, and concavity. Analysis of this data is very much useful in the prediction of the stage of cancer in Lung cancer patients. This project aims at analyzing the lung cancer cell data set and making a prediction for the given data using ada boost classifier and multi-layer perceptron deep learning classifier.