gradient-boosting | Topic | Ecosyste.ms: Repos

Topic: "gradient-boosting"

shap/shap

A game theoretic approach to explain the output of any machine learning model.

Language: Jupyter Notebook - Size: 301 MB - Last synced at: 5 days ago - Pushed at: 9 days ago - Stars: 23,820 - Forks: 3,359

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Language: C++ - Size: 23.2 MB - Last synced at: 5 days ago - Pushed at: 8 days ago - Stars: 17,175 - Forks: 3,875

ddbourgin/numpy-ml

Machine learning, in numpy

Language: Python - Size: 10 MB - Last synced at: 17 days ago - Pushed at: over 1 year ago - Stars: 16,067 - Forks: 3,801

EpistasisLab/tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Language: Jupyter Notebook - Size: 86.9 MB - Last synced at: 2 days ago - Pushed at: 8 days ago - Stars: 9,897 - Forks: 1,578

catboost/catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Language: C++ - Size: 1.66 GB - Last synced at: 5 days ago - Pushed at: 6 days ago - Stars: 8,378 - Forks: 1,217

interpretml/interpret

Fit interpretable models. Explain blackbox machine learning.

Language: C++ - Size: 14.7 MB - Last synced at: 2 days ago - Pushed at: 16 days ago - Stars: 6,483 - Forks: 746

benedekrozemberczki/awesome-decision-tree-papers

A collection of research papers on decision, classification and regression trees with implementations.

Language: Python - Size: 870 KB - Last synced at: 3 days ago - Pushed at: about 1 year ago - Stars: 2,399 - Forks: 343

stanfordmlgroup/ngboost

Natural Gradient Boosting for Probabilistic Prediction

Language: Python - Size: 12 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 1,703 - Forks: 233

benedekrozemberczki/awesome-fraud-detection-papers

A curated list of data mining papers about fraud detection.

Language: Python - Size: 490 KB - Last synced at: 10 days ago - Pushed at: about 1 year ago - Stars: 1,693 - Forks: 311

ClimbsRocks/auto_ml

[UNMAINTAINED] Automated machine learning for analytics & production

Language: Python - Size: 1.38 MB - Last synced at: 27 days ago - Pushed at: about 4 years ago - Stars: 1,644 - Forks: 312

benedekrozemberczki/awesome-gradient-boosting-papers

A curated list of gradient boosting research papers with implementations.

Language: Python - Size: 1.48 MB - Last synced at: 3 days ago - Pushed at: about 1 year ago - Stars: 1,022 - Forks: 160

TorchEnsemble-Community/Ensemble-Pytorch

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

Language: Python - Size: 1.56 MB - Last synced at: 4 days ago - Pushed at: 11 months ago - Stars: 1,020 - Forks: 94

sberbank-ai-lab/LightAutoML 📦

LAMA - automatic model creation framework

Language: Python - Size: 23.4 MB - Last synced at: 10 days ago - Pushed at: about 3 years ago - Stars: 925 - Forks: 96

Freemanzxp/GBDT_Simple_Tutorial

python实现GBDT的回归、二分类以及多分类，将算法流程详情进行展示解读并可视化，庖丁解牛地理解GBDT。Gradient Boosting Decision Trees regression, dichotomy and multi-classification are realized based on python, and the details of algorithm flow are displayed, interpreted and visualized to help readers better understand Gradient Boosting Decision Trees

Language: Python - Size: 2.13 MB - Last synced at: 6 months ago - Pushed at: almost 6 years ago - Stars: 723 - Forks: 196

tensorflow/decision-forests

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

Language: Python - Size: 5.87 MB - Last synced at: 3 days ago - Pushed at: about 1 month ago - Stars: 680 - Forks: 113

x4nth055/emotion-recognition-using-speech

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Language: Python - Size: 944 MB - Last synced at: 29 days ago - Pushed at: over 1 year ago - Stars: 621 - Forks: 242

zygmuntz/hyperband

Tuning hyperparams fast with Hyperband

Language: Python - Size: 370 KB - Last synced at: about 1 month ago - Pushed at: over 6 years ago - Stars: 593 - Forks: 72

google/yggdrasil-decision-forests

A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

Language: C++ - Size: 39.5 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 569 - Forks: 60

serengil/chefboost

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

Language: Python - Size: 1.09 MB - Last synced at: 29 days ago - Pushed at: about 1 month ago - Stars: 472 - Forks: 101

perpetual-ml/perpetual

A self-generalizing gradient boosting machine that doesn't need hyperparameter optimization

Language: Rust - Size: 792 KB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 468 - Forks: 24

siboehm/lleaves

Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.

Language: Python - Size: 4.75 MB - Last synced at: 4 days ago - Pushed at: 5 days ago - Stars: 417 - Forks: 33

elucideye/drishti

Real time eye tracking for embedded and mobile devices.

Language: C++ - Size: 12.2 MB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 396 - Forks: 83

rickiepark/handson-ml Fork of ageron/handson-ml

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Language: Jupyter Notebook - Size: 146 MB - Last synced at: over 1 year ago - Pushed at: about 5 years ago - Stars: 288 - Forks: 279

EpistasisLab/tpot2

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Language: Jupyter Notebook - Size: 5.3 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 186 - Forks: 26

cheng-li/pyramid

Open source Machine Learning library written in Java

Language: Java - Size: 4.81 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 186 - Forks: 54

arogozhnikov/infiniteboost

InfiniteBoost: building infinite ensembles with gradient descent

Language: Jupyter Notebook - Size: 4.65 MB - Last synced at: 27 days ago - Pushed at: over 6 years ago - Stars: 184 - Forks: 23

Evovest/EvoTrees.jl

Boosted trees in Julia

Language: Julia - Size: 46.7 MB - Last synced at: 6 days ago - Pushed at: 14 days ago - Stars: 182 - Forks: 22

feedzai/fairgbm

Train Gradient Boosting models that are both high-performance *and* Fair!

Language: C++ - Size: 43 MB - Last synced at: 4 days ago - Pushed at: 11 months ago - Stars: 104 - Forks: 6

benedekrozemberczki/tigerlily

TigerLily: Finding drug interactions in silico with the Graph.

Language: Jupyter Notebook - Size: 14.3 MB - Last synced at: 29 days ago - Pushed at: over 2 years ago - Stars: 99 - Forks: 9

soda-inria/hazardous

Competing Risks and Survival Analysis

Language: Python - Size: 9.2 MB - Last synced at: 26 days ago - Pushed at: 26 days ago - Stars: 94 - Forks: 17

qiyiping/gbdt

Language: C++ - Size: 597 KB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 94 - Forks: 70

pfnet-research/autogbt-alt

An experimental Python package that reimplements AutoGBT using LightGBM and Optuna.

Language: Python - Size: 171 KB - Last synced at: 28 days ago - Pushed at: about 6 years ago - Stars: 82 - Forks: 11

Timur-Maistermind/Machine-Learning-Roadmap

Machine Learning Roadmap for 2025. Step-by-step guide to become a Data Scientist. Covers the best free learning resources from Python basics to Deep Learning and MLOps.

Size: 3.72 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 73 - Forks: 5

bsharchilev/influence_boosting

Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"

Language: Python - Size: 16.1 MB - Last synced at: about 1 month ago - Pushed at: 12 months ago - Stars: 67 - Forks: 18

Blunde1/agtboost

Adaptive and automatic gradient boosting computations.

Language: R - Size: 6.11 MB - Last synced at: 6 months ago - Pushed at: over 2 years ago - Stars: 67 - Forks: 11

serengil/decision-trees-for-ml

Building Decision Trees From Scratch In Python

Language: Jupyter Notebook - Size: 371 KB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 66 - Forks: 51

sh1ng/arboretum

Gradient Boosting powered by GPU(NVIDIA CUDA)

Language: Cuda - Size: 656 KB - Last synced at: 25 days ago - Pushed at: about 5 years ago - Stars: 64 - Forks: 14

closest-git/LiteMORT

A memory efficient GBDT on adaptive distributions. Much faster than LightGBM with higher accuracy. Implicit merge operation.

Language: C++ - Size: 1.47 MB - Last synced at: 3 days ago - Pushed at: about 5 years ago - Stars: 58 - Forks: 9

rmitsuboshi/miniboosts

A collection of boosting algorithms written in Rust 🦀

Language: Rust - Size: 4.12 MB - Last synced at: 28 days ago - Pushed at: 3 months ago - Stars: 52 - Forks: 5

lamres/orderbook_modeling

Example of order book modeling.

Language: Jupyter Notebook - Size: 19 MB - Last synced at: about 1 year ago - Pushed at: almost 6 years ago - Stars: 52 - Forks: 34

RubixML/Housing

An example project that predicts house prices for a Kaggle competition using a Gradient Boosted Machine.

Language: PHP - Size: 617 KB - Last synced at: 6 days ago - Pushed at: over 2 years ago - Stars: 51 - Forks: 22

aertslab/arboreto

A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.

Language: Jupyter Notebook - Size: 63.9 MB - Last synced at: 11 months ago - Pushed at: about 1 year ago - Stars: 47 - Forks: 24

G-U-N/ECCV22-FOSTER

The official implementation for ECCV22 paper: "FOSTER: Feature Boosting and Compression for Class-Incremental Learning" in PyTorch.

Language: Python - Size: 4.03 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 47 - Forks: 3

blei-lab/treeffuser

Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression on tabular data with tree-based diffusion models.

Language: Jupyter Notebook - Size: 80.3 MB - Last synced at: 17 days ago - Pushed at: 3 months ago - Stars: 43 - Forks: 4

rishiraj/autolgbm

LightGBM + Optuna: Auto train LightGBM directly from CSV files, Auto tune them using Optuna, Auto serve best model using FastAPI. Inspired by Abhishek Thakur's AutoXGB.

Language: Python - Size: 1.06 MB - Last synced at: 17 days ago - Pushed at: about 3 years ago - Stars: 37 - Forks: 5

benedekrozemberczki/BoostedFactorization

An implementation of "Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation" (ASONAM 2019).

Language: Python - Size: 829 KB - Last synced at: 29 days ago - Pushed at: over 2 years ago - Stars: 36 - Forks: 13

jd-opensource/UTBoost

A powerful tree-based uplift modeling system.

Language: C++ - Size: 188 KB - Last synced at: 20 days ago - Pushed at: over 1 year ago - Stars: 30 - Forks: 2

TomerRonen34/treeboost_autograd

Easy Custom Losses for Tree Boosters using Pytorch

Language: Python - Size: 32.2 KB - Last synced at: 5 months ago - Pushed at: about 4 years ago - Stars: 30 - Forks: 6

KwokHing/YandexCatBoost-Python-Demo

Demo on the capability of Yandex CatBoost gradient boosting classifier on a fictitious IBM HR dataset obtained from Kaggle. Data exploration, cleaning, preprocessing and model tuning are performed on the dataset

Language: Jupyter Notebook - Size: 743 KB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 30 - Forks: 16

RektPunk/MQBoost

Multiple quantiles estimation model maintaining non-crossing condition (or monotone quantile condition) using LightGBM and XGBoost

Language: Python - Size: 752 KB - Last synced at: 9 days ago - Pushed at: 6 months ago - Stars: 29 - Forks: 5

MaxHalford/starboost

:star::rocket: Gradient boosting on steroids

Language: Python - Size: 231 KB - Last synced at: 10 days ago - Pushed at: 11 months ago - Stars: 28 - Forks: 10

reneleogp/ML-Prediction-LoL

In this project I implemented two machine learning algorithms to predicts the outcome of a League of Legends game.

Language: Jupyter Notebook - Size: 13.1 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 28 - Forks: 3

haghish/mlim

mlim: single and multiple imputation with automated machine learning

Language: R - Size: 2.41 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 26 - Forks: 1

StatMixedML/DGBM

Distributional Gradient Boosting Machines

Size: 169 KB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 26 - Forks: 1

MMBazel/Classifying-Sales-Calls

Turning salesforce lead, oppty, & sales activities data => Sales predictions using pandas, Scikit-learn, SQLAlchemy, Redshift, XGBoost Classifier

Language: Jupyter Notebook - Size: 6.95 MB - Last synced at: about 1 month ago - Pushed at: about 4 years ago - Stars: 26 - Forks: 9

rickiepark/handson-gb

XGBoost와 사이킷런으로 배우는 그레이디언트 부스팅

Language: Jupyter Notebook - Size: 185 MB - Last synced at: about 1 month ago - Pushed at: 2 months ago - Stars: 25 - Forks: 21

nanxstats/stackgbm

🌳 Stacked Gradient Boosting Machines

Language: R - Size: 1.91 MB - Last synced at: 5 days ago - Pushed at: about 1 year ago - Stars: 25 - Forks: 1

harshraj11584/Paper-Implementation-Overview-Gradient-Descent-Optimization-Sebastian-Ruder

[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder

Language: Python - Size: 58.6 KB - Last synced at: 11 months ago - Pushed at: about 6 years ago - Stars: 22 - Forks: 6

sibirbil/RuleDiscovery

Two algorithms based on linear programming to discover classification rules for interpretable learning.

Language: Python - Size: 89 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 21 - Forks: 1

serengil/h2o-ai-101

This repository covers h2o ai based implementations

Language: Jupyter Notebook - Size: 1.59 MB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 21 - Forks: 5

nickkunz/nestedhyperboost

Nested Cross-Validation for Bayesian Optimized Gradient Boosting

Language: Python - Size: 2.89 MB - Last synced at: 22 days ago - Pushed at: about 5 years ago - Stars: 20 - Forks: 2

mrapp-ke/Boomer 📦

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-label Classification Rules

Size: 200 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 19 - Forks: 3

radiantearth/model_ecaas_agrifieldnet_gold

AgriFieldNet Model for Crop Detection from Satellite Imagery

Language: Python - Size: 588 MB - Last synced at: 29 days ago - Pushed at: over 2 years ago - Stars: 19 - Forks: 4

compgeolab/eql-gradient-boosted

Paper: Gradient-boosted equivalent sources method for interpolating very large gravity and magnetic datasets

Language: Jupyter Notebook - Size: 364 MB - Last synced at: 11 months ago - Pushed at: over 3 years ago - Stars: 19 - Forks: 6

mratsim/Apartment-Interest-Prediction

Predict people interest in renting specific NYC apartments. The challenge combines structured data, geolocalization, time data, free text and images.

Language: Jupyter Notebook - Size: 440 KB - Last synced at: 4 days ago - Pushed at: over 7 years ago - Stars: 18 - Forks: 1

ottenbreit-data-science/aplr

APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering smoother and interpretable predictions.

Language: C++ - Size: 6.13 MB - Last synced at: 23 days ago - Pushed at: 24 days ago - Stars: 17 - Forks: 4

motapinto/football-classification-predications

Supervised Learning Models used to predict outcomes of football matches

Language: Jupyter Notebook - Size: 119 MB - Last synced at: 26 days ago - Pushed at: almost 4 years ago - Stars: 17 - Forks: 9

andremonaco/cheapml

Machine Learning algorithms coded from scratch

Language: R - Size: 69.3 KB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 17 - Forks: 11

davemlz/water-storage-retrieval

Semi-supervised water storage retrieval using Sentinel-2

Language: Jupyter Notebook - Size: 288 MB - Last synced at: 17 days ago - Pushed at: almost 5 years ago - Stars: 17 - Forks: 5

aertslab/GRNBoost 📦

Scalable inference of gene regulatory networks using Apache Spark and XGBoost

Language: Scala - Size: 3.87 MB - Last synced at: 6 months ago - Pushed at: over 7 years ago - Stars: 17 - Forks: 3

adamingas/ordinalgbt

A package to build Gradient boosted trees for ordinal labels

Language: Jupyter Notebook - Size: 625 KB - Last synced at: 8 days ago - Pushed at: about 1 month ago - Stars: 16 - Forks: 1

ThomasWong2022/thor-public

AutoML tools for solving Time-Varying High-Dimensional Ordinal Regression Problems

Language: Python - Size: 3.03 MB - Last synced at: 4 months ago - Pushed at: over 1 year ago - Stars: 16 - Forks: 3

LailaMahmoudi/Breast-Cancer-Predictions-With-SVM

Implementation of SVM Classifier To Perform Classification on the dataset of Breast Cancer Wisconin; to predict if the tumor is cancer or not.

Language: Jupyter Notebook - Size: 2.83 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 16 - Forks: 5

xRiskLab/xBooster

Explainable Boosted Scoring with Python: turning XGBoost and CatBoost classifiers into explainable scorecards

Language: Python - Size: 7.52 MB - Last synced at: 12 days ago - Pushed at: 21 days ago - Stars: 14 - Forks: 4

qinhanmin2014/kaggle-bike-sharing-demand

simple solution based on Gradient Boost and Random Forest, rank 24/3251 (top 1%) within 60 lines of python code

Language: Jupyter Notebook - Size: 2.47 MB - Last synced at: 4 days ago - Pushed at: almost 6 years ago - Stars: 14 - Forks: 11

mirecl/catboost-cgo

CatBoost a fast, scalable, high performance Gradient Boosting on Decision Trees library. Golang using Cgo for blazing fast inference CatBoost Model 🚀

Language: C - Size: 798 KB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 13 - Forks: 1

mavillan/tsforest

Time series forecasting with tree ensembles

Language: Python - Size: 240 KB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 13 - Forks: 3

LaxmiChaudhary/Modeling-of-strength-of-high-performance-concrete-using-Machine-Learning

Language: Jupyter Notebook - Size: 1.56 MB - Last synced at: 8 months ago - Pushed at: over 5 years ago - Stars: 13 - Forks: 10

Vikranth3140/Movie-Revenue-Prediction

Movie Revenue Prediction System predicts the revenue of a movie with 14 parameters: name, rating, genre, year, released, score, votes, director, writer, star, country, budget, company and runtime using gradient boosting______________________________ Training Accuracy: 91.58%____________ Testing Accuracy: 82.42%.

Language: TeX - Size: 27.9 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 12 - Forks: 5

yandex-research/tabgraphs

A benchmark of meaningful graph datasets with tabular node features

Language: Python - Size: 138 KB - Last synced at: about 2 months ago - Pushed at: 3 months ago - Stars: 12 - Forks: 1

erdogant/treeplot

Plot tree based machine learning models

Language: Python - Size: 31.5 MB - Last synced at: 25 days ago - Pushed at: 7 months ago - Stars: 12 - Forks: 2

alifrmf/Mobile-Price-Prediction-Classification-Analysis

Supervised Machine Learning Analysis Using Classification Models

Language: Jupyter Notebook - Size: 14.6 MB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 12 - Forks: 1

chaitjo/working-women

Code for the paper 'Working Women and Caste in India' (ICLR 2019 AI for Social Good Workshop)

Language: Jupyter Notebook - Size: 212 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 12 - Forks: 2

dksifoua/Stock-Market-Prediction

Stock Market Prediction on High-Frequency Data Using soft computing based AI models

Language: Jupyter Notebook - Size: 415 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 12 - Forks: 8

BerkKilicoglu/ML-Modelling-Disease-Analysis

Obtaining meaningful results from the data set using the model trained with machine learning methods.

Language: Python - Size: 5.14 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 11 - Forks: 1

IDRnD/antispoofing-features

Code for the paper "Bag of features for voice anti-spoofing"

Language: Python - Size: 257 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 11 - Forks: 2

MrKhan0747/Heart-Disease-Detection

Machine learning model to detect heart attack. Various techinques applied data cleaning, visualization, and modeling

Language: Jupyter Notebook - Size: 627 KB - Last synced at: over 1 year ago - Pushed at: about 6 years ago - Stars: 11 - Forks: 9

jeremiedb/EvoLinear.jl

Linear models

Language: Julia - Size: 427 KB - Last synced at: 6 days ago - Pushed at: 11 months ago - Stars: 10 - Forks: 1

somjit101/Facebook-Friend-Recommendation

This is a friend recommendation systems which are used on social media platforms (e.g. Facebook, Instagram, Twitter) to suggest friends/new connections based on common interests, workplace, common friends etc. using Graph Mining techniques. Here, we are given a social graph, i.e. a graph structure where nodes are individuals on social media platforms and a directed edges (or 'links') indicates that one person 'follows' the other, or are 'friends' on social media. Now, the task is to predict newer edges to be offered as 'friend suggestions'.

Language: Jupyter Notebook - Size: 770 KB - Last synced at: 19 days ago - Pushed at: about 1 year ago - Stars: 10 - Forks: 3