Data-Visualisation

Information Retrieval Project

This project aims to evaluate and compare the performance of various classification models trained on a medical EEG dataset, to tell which model is better at retrieving information from unseen dataset. I created generic modules which take in any dataset and visualize the model performances. You can use different datasets and compare the performace of various classification models used here.

Classification models used here:

Gaussian Naive Bayes

K Neighbours

Logistic Regression

Random Forest

Decision Tree

Support Vector Machine (SVM)

Model perfomances on various parameters

gain lift charts