All Relevant Feature Selection

This repository contains an ML workflow to predict house prices in Ames, Iowa. This project work is carried out under the Machine Learning module of the GeoDSc track of the Copernicus Master in Digital Earth.

Modelling and prediction of default + deployment via AWS Sagemaker

Data Mining exercise of epitope prediction and classification of virus based on protein data

Migrated to GitLab

Identify the most important variables that contribute to the level of sustainability of schools using supervised machine learning. Use the importance to assign a weight to each characteristic and calculate a sustainability index for each school.

Feature selection on a Bitcoin Dataset

Sales Prediction for Rossmann Pharmaceutics database using Machine Learning regression modeling

A Credit Limit Classification Business Problem. We need to develop a model in 2 days to predict if a bank should concede or not give a higher credit limit to its clients.

Machine learning model developed in R to predict which water pumps across Tanzania are not working properly

The feature of interest is whether or not a customer buys a caravan insurance, based on socio-demographic factors and ownership of other insurance policies; and to build profile of a typical customer.

A fast xgboost feature selection algorithm

This repository proposes several methods to infer relevant associations within a set of features.

Credit Scoring from inputs to interpretation, see Streamlit_app repo to get to the dashboard

Feature selection project for a student competition. Analyzing data for chemists at University of Southampton.

All-relevant feature selection with Boruta, Shiny and R

CART, K-Means, Apriori, Adaboost, RFE; models using Anti-cancer peptides vs Human proteins

Project made for Advanced Methods in Machine Learning subject at MINI PW

Classification model using R to predict the biodegradability of various chemicals

Analytical tool to help the company decide whether the employee will stay or not