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16 search results found

Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.

Imbalanced Ensemble ⭐ 234

Class-imbalanced Ensemble Learning in Python. | 类别不平衡/长尾机器学习库

Self Paced Ensemble ⭐ 217

ICDE'20 | A general & effective ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架

Open Solution Toxic Comments ⭐ 151

Open solution to the Toxic Comment Classification Challenge

💪 🤔 Modern Super Learning with Machine Learning Pipelines

Spot Rna ⭐ 58

RNA Secondary Structure Prediction using an Ensemble of Two-dimensional Deep Neural Networks and Transfer Learning.

hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating the results on an independent validation set. hgboost can be applied for classification and regression tasks.

Open Solution Value Prediction ⭐ 39

Open solution to the Santander Value Prediction Challenge 🐠

Forecastveg ⭐ 34

A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python

Disentangled Attribution Curves ⭐ 23

Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"

Kgem Ensembles In Drug Discovery ⭐ 17

Source code and data repository for "Ensembles of knowledge graph embedding models improve predictions for drug discovery"

Stacking Blending Voting Ensembles ⭐ 15

This repository contains an example of each of the Ensemble Learning methods: Stacking, Blending, and Voting. The examples for Stacking and Blending were made from scratch, the example for Voting was using the scikit-learn utility.

Yelp Recommendation System ⭐ 10

Recommend Restaurants to User based on the ratings given by them to the restaurants

Churnbabychurn ⭐ 9

Telco Churn - Ensemble and Stacked Classifer Models

An updated R package deeper: Deep Ensemble for Environmental Predictor

Multiple Model Ensembling

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