ensemble-learning

There are 26 repositories under ensemble-learning topic.

autogluon
autogluon / autogluon
Fast and Accurate ML in 3 Lines of Code
automl machine-learning data-science deep-learning ensemble-learning computer-vision natural-language-processing structured-data object-detection gluon transfer-learning pytorch automated-machine-learning scikit-learn autogluon tabular-data hyperparameter-optimization time-series forecasting python
Language:Python 9562
MingchaoZhu / DeepLearning
Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
bayesian deep-learning ensemble-learning machine-learning python regularization xgboost
Language:Python 7400
h2oai / h2o-3
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
h2o machine-learning data-science deep-learning big-data ensemble-learning gbm random-forest naive-bayes pca opensource distributed java python r hadoop spark gpu automl h2o-automl
Language:Jupyter Notebook 7357
BoltzmannEntropy / interviews.ai
It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.
artificial-intelligence autograd bayesian-statistics convolutional-neural-networks data-science deep-learning ensemble-learning feature-extraction graduate-school information-theory interview-preparation jax jobs logistic-regression loss-functions machine-learning python pytorch pytorch-tutorial
4726
salesforce / Merlion
Merlion: A Machine Learning Framework for Time Series Intelligence
anomaly-detection automl benchmarking ensemble-learning forecasting machine-learning time-series
Language:Python 4441
awesome-decision-tree-papers
benedekrozemberczki / awesome-decision-tree-papers
A collection of research papers on decision, classification and regression trees with implementations.
cart catboost classification-model classification-trees classifier decision-tree decision-tree-classifier decision-tree-learning decision-tree-model ensemble-learning gradient-boosting gradient-boosting-machine lightgbm machine-learning machine-learning-research random-forest regression-tree statistical-learning tree-ensemble xgboost
Language:Python 2431
JuliaAI / MLJ.jl
A Julia machine learning framework
classification clustering data-science ensemble-learning julia machine-learning pipeline pipelines predictive-modeling regression stacking statistics tuning tuning-parameters
Language:Julia 1880
justmarkham / DAT8
General Assembly's 2015 Data Science course in Washington, DC
data-science machine-learning scikit-learn data-analysis pandas jupyter-notebook python course linear-regression logistic-regression model-evaluation naive-bayes natural-language-processing decision-trees ensemble-learning clustering regular-expressions web-scraping data-visualization data-cleaning
Language:Jupyter Notebook 1615
awesome-imbalanced-learning
ZhiningLiu1998 / awesome-imbalanced-learning
😎 Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切：论文、代码、框架与库
awesome awesome-list class-imbalance deep-learning ensemble-learning fair-ml fairness-ml imbalanced-classes imbalanced-classification imbalanced-data imbalanced-learning machine-learning skewed-data
1495
kingfengji / gcForest
This is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'
machine-learning random-forest ensemble-learning deep-forest
Language:Python 1310
xcessiv
reiinakano / xcessiv
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
automated-machine-learning data-science ensemble-learning hyperparameter-optimization machine-learning scikit-learn stacked-ensembles
Language:Python 1266
TorchEnsemble-Community / Ensemble-Pytorch
A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.
pytorch pytorch-tutorial ensemble-learning ensemble deeplearning neural-networks deep-learning gradient-boosting voting-classifier bagging
Language:Python 1037
Minqi824 / ADBench
Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.
anomaly-detection benchmark data-mining deep-learning machine-learning outlier-detection semi-supervised-learning supervised-learning unsupervised-learning data-sicence ensemble-learning neural-networks python
Language:Python 992
LAMDA-NJU / Deep-Forest
An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)
deep-forest ensemble-learning machine-learning python random-forest
Language:Python 953
shubhomoydas / ad_examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
ensemble-learning active-learning anomaly-detection rnn lstm explaination interpretability time-series timeseries trees unsuperivsed autoencoder streaming concept-drift generative-adversarial-network gan anogan graph-convolutional-networks adversarial-attacks nettack
Language:Python 865
flennerhag / mlens
ML-Ensemble – high performance ensemble learning
ensemble-learning machine-learning ensemble learners stacking stack ensembles python
Language:Python 860
vecxoz / vecstack
Python package for stacking (machine learning technique)
stacking stacked-generalization explain-stacking stacking-tutorial blending bagging ensembling ensemble ensemble-learning machine-learning
Language:Python 700
yzhao062 / combo
(AAAI' 20) A Python Toolbox for Machine Learning Model Combination
machine-learning data-mining data-science ensemble-learning python model-combination aggregation pipeline-framework machine-learning-pipelines
Language:Python 657
EnnengYang / Awesome-Model-Merging-Methods-Theories-Applications
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
attack-defense continual-learning diffusion-models ensemble-learning federated-learning few-shot-learning foundation-models generalization generative-model knowledge-fusion large-language-models llms meta-learning model-fusion model-merging multi-domain-learning multi-task-learning robustness transfer-learning zero-shot-learning
590
Western-OC2-Lab / Intrusion-Detection-System-Using-Machine-Learning
Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
autonomous-vehicles bayesian-optimization catboost cicids2017 cyber-security decision-tree ensemble-learning hpo hyperparameter-optimization intrusion-detection intrusion-detection-system kmeans lightgbm machine-learning network-security python-examples random-forest stacking xgboost
Language:Jupyter Notebook 539
scikit-learn-contrib / DESlib
A Python library for dynamic classifier and ensemble selection
ensemble-learning ensemble-selection ensemble-prediction dynamic-ensembles dynamic-selection diversity diversity-measures classifier-ensembles
Language:Python 493
kk7nc / RMDL
RMDL: Random Multimodel Deep Learning for Classification
classification cnn convolutional-neural-networks data-mining deep-learning deep-neural-networks dnn ensemble-learning image-classification information-retrieval keras machine-learning multimodel recurrent-neural-networks rnn tensorflow text-classification text-mining
Language:Python 433
ampyfin
AmpyFin / ampyfin
End-to-end ensemble trading framework that trains, backtests, and promotes validated strategies to live execution.
finance machine-learning python trading-algorithms trading-bot trading-strategies algo-trading ensemble-learning algorithmic-trading open-source trade
Language:Python 424
mdabros / SharpLearning
Machine learning for C# .Net
machine-learning csharp decision-trees adaboost gradient-boosting-machine random-forest neural-nets deep-learning ensemble-learning cross-validation metrics dotnet machine learning opensource
Language:C# 401
ledell / useR-machine-learning-tutorial
useR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive http://user2016.org/tutorials/10.html
machine-learning deep-learning random-forest gradient-boosting-machine tutorial data-science ensemble-learning r
Language:Jupyter Notebook 399
imbalanced-ensemble
ZhiningLiu1998 / imbalanced-ensemble
🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库
class-imbalance classification data-mining data-science ensemble ensemble-imbalanced-learning ensemble-learning ensemble-model imbalanced-classification imbalanced-data imbalanced-learning long-tail machine-learning multi-class-classification python python3 scikit-learn sklearn
Language:Python 399
IBM / AutoMLPipeline.jl
A package that makes it trivial to create and evaluate machine learning pipeline architectures.
pipeline pipeline-structure machine-learning automl symbolic-expressions data-mining julia scikitlearn-wrapper symbolic-pipeline pipeline-optimization ensemble-learning chaining stacking data-mining-algorithms data-science machine-learning-models classification
Language:Julia 368
DataCanvasIO / HyperGBM
A full pipeline AutoML tool for tabular data
adversarial-validation automl catboost dask dask-distributed datacleaning distributed-training ensemble-learning fullpipeline gbm gpu-acceleration lightgbm preprocessing pseudo-labeling rapidsai semi-supervised-learning sklearn tabular-data xgboost
Language:Python 358
yzhao062 / awesome-ensemble-learning
Ensemble learning related books, papers, videos, and toolboxes
machine-learning data-mining ensemble-learning ensembling data-science
Language:Python 300
rickiepark / handson-ml
도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.
deep-learning machine-learning tensorflow scikit-learn python neural-network recurrent-neural-networks reinforcement-learning autoencoder deep-neural-networks ensemble-learning svm random-forest gradient-boosting xgboost
Language:Jupyter Notebook 291
moon-hotel / MachineLearningWithMe
A repository contains more than 12 common statistical machine learning algorithm implementations. 常见10余种机器学习算法原理与实现及视频讲解。@月来客栈出品
machine-learning adaboost clustering machine-learning-algorithms naive-bayes python cart decision-tree-classifier kd-tree knn pca svm svm-classifier dbscan-clustering ensemble-learning gbdt hca hierarchical-clustering self-training
Language:Jupyter Notebook 281
self-paced-ensemble
ZhiningLiu1998 / self-paced-ensemble
[ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架
class-imbalance classification ensemble ensemble-learning ensemble-methods ensemble-model imbalance-classification imbalanced-data imbalanced-learn imbalanced-learning machine-learning pypi python3
Language:Python 259
skggm / skggm
Scikit-learn compatible estimation of general graphical models
scikit-learn machine-learning graphical-models gaussian-graphical-models covariance-matrix ensemble-learning nonparametric rank-correlation general-graphical-models skggm graphical-lasso precision-matrix concentration-graph
Language:Python 247
ikki407 / stacking
Stacked Generalization (Ensemble Learning)
ensemble ensemble-learning prediction scikit-learn stacking xgboost
Language:Python 227
shapley
benedekrozemberczki / shapley
The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
shapley shapley-value owen voting-classifier machine-learning classifier random-forest random-forest-classifier explainable-ml explainable-ai ensemble ensemble-learning deep-learning voting-game game-theory game-theory-toolbox weighted-voting-games
Language:Python 221
Western-OC2-Lab / PWPAE-Concept-Drift-Detection-and-Adaptation
Data stream analytics: Implement online learning methods to address concept drift and model drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams" published in IEEE GlobeCom 2021.
adaptive-learning anomaly-detection change-detector cicids2017 concept-drift data-stream drift drift-detection ensemble-learning intrusion-detection-system iot iot-data-analytics lightgbm machine-learning online-learning real-time-analytics streaming-data
Language:Jupyter Notebook 217

ensemble-learning

autogluon / autogluon

MingchaoZhu / DeepLearning

h2oai / h2o-3

BoltzmannEntropy / interviews.ai

salesforce / Merlion

benedekrozemberczki / awesome-decision-tree-papers

JuliaAI / MLJ.jl

justmarkham / DAT8

ZhiningLiu1998 / awesome-imbalanced-learning

kingfengji / gcForest

reiinakano / xcessiv

TorchEnsemble-Community / Ensemble-Pytorch

Minqi824 / ADBench

LAMDA-NJU / Deep-Forest

shubhomoydas / ad_examples

flennerhag / mlens

vecxoz / vecstack

yzhao062 / combo

EnnengYang / Awesome-Model-Merging-Methods-Theories-Applications

Western-OC2-Lab / Intrusion-Detection-System-Using-Machine-Learning

scikit-learn-contrib / DESlib

kk7nc / RMDL

AmpyFin / ampyfin

mdabros / SharpLearning

ledell / useR-machine-learning-tutorial

ZhiningLiu1998 / imbalanced-ensemble

IBM / AutoMLPipeline.jl

DataCanvasIO / HyperGBM

yzhao062 / awesome-ensemble-learning

rickiepark / handson-ml

moon-hotel / MachineLearningWithMe

ZhiningLiu1998 / self-paced-ensemble

skggm / skggm

ikki407 / stacking

benedekrozemberczki / shapley

Western-OC2-Lab / PWPAE-Concept-Drift-Detection-and-Adaptation