A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).

[ECCV-20] Official PyTorch implementation of HoughNet, a voting-based object detector.

Contains code for a voting classifier that is part of an ensemble learning model for tweet classification (which includes an LSTM, a bayesian model and a proximity model) and a system for weighted voting

In this project, the success results obtained from SVM, KNN and Decision Tree Classifier algorithms using the data we have created and the results obtained from the ensemble learning methods Random Forest Classifier, AdaBoost and Voting were compared.

A mobile application that diagnoses Parkinson’s disease patients using hand drawings

A machine learning model that predicts whether an email is spam or not.

Forecasting the likelihood of a customer defaulting their auto loan using classification models

In this project, algorithms such as Svm, Knn, Decision Tree were trained and performance results were recorded with the data sets we created. Later, community learning algorithms such as Random Forest, AdaBoost and Voting were trained, performance results were recorded and these performance results were compared and analyzed.

A novel ML-based binary classifier to tell viral and non-viral long reads apart in metagenomic samples.

The goal of this project was used advanced preprocessing and feature engineering. Achieved high accuracy with XGBoost and LightGBM. Deployed via a Django web application and visualization was presented using Dash and Plotly.

This is a weighted blending machine implemented using a neural network. The advantage of using a neural network is that the weights assigned to the models for the final result is assigned by the neural network based on backpropagation.

Document Classification using Python and scikit-learn and nltk

A visual approach to understand the beauty of voting classifiers

A collection of 3 deep learning models working together to predict people emotions through a voting classifier that comes with two strategies : "soft" and "hard".

Voting Ensemble & Stock Prediction - Project Submission for Data Mining & Machine Learning Module

Built a classifier for evaluating quality of machine translation to predict best matching sentence to the reference sentence

Titanic