Cancerous Tumor Classifier based on RNA-Seq gene expressions dataset.
It uses the 'gene expression cancer RNA-Seq Data Set' to create classification models using six different algorithms - Logistic Regression, Linear Discriminant Analysis, K-Nearest Neighbors, Classification and Regression Trees, Gaussian Naive Bayes, Support Vector Machines.
It then compares the performace of these algorithms by using K-Fold cross-validation. Performs classification with an accuracy of > 97%
Dataset available at https://archive.ics.uci.edu/ml/datasets/gene+expression+cancer+RNA-Seq .
Implemented using help from - https://machinelearningmastery.com/ , http://scikit-learn.org/stable/tutorial/index.html