random-forest
There are 9300 repositories under random-forest topic.
EpistasisLab/tpot
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
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.
biolab/orange3
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
susanli2016/Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
microsoft/FLAML
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
tirthajyoti/Machine-Learning-with-Python
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
mljar/mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
parrt/dtreeviz
A python library for decision tree visualization and model interpretation.
benedekrozemberczki/awesome-decision-tree-papers
A collection of research papers on decision, classification and regression trees with implementations.
szilard/benchm-ml
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
kk7nc/Text_Classification
Text Classification Algorithms: A Survey
benedekrozemberczki/awesome-fraud-detection-papers
A curated list of data mining papers about fraud detection.
lxztju/pytorch_classification
利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码
kingfengji/gcForest
This is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'
LiYangHart/Hyperparameter-Optimization-of-Machine-Learning-Algorithms
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
nivu/ai_all_resources
A curated list of Best Artificial Intelligence Resources
automl/SMAC3
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
grf-labs/grf
Generalized Random Forests
benedekrozemberczki/awesome-gradient-boosting-papers
A curated list of gradient boosting research papers with implementations.
LAMDA-NJU/Deep-Forest
An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)
nickgillian/grt
gesture recognition toolkit
Xtra-Computing/thundergbm
ThunderGBM: Fast GBDTs and Random Forests on GPUs
tensorflow/decision-forests
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
emlearn/emlearn
Machine Learning inference engine for Microcontrollers and Embedded devices
google/yggdrasil-decision-forests
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
linkedin/FastTreeSHAP
Fast SHAP value computation for interpreting tree-based models
machinelearnjs/machinelearnjs
Machine Learning library for the web and Node.
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..)
kLabUM/rrcf
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
mljar/supertree
Visualize decision trees in Python
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
kochlisGit/ProphitBet-Soccer-Bets-Predictor
ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using Advanced Machine Learning (ML) methods. The supported algorithms in this application are Neural Networks, Random Forests & Ensembl Models.
zhaoxingfeng/RandomForest
随机森林，Random Forest（RF）
Skylark0924/Machine-Learning-is-ALL-You-Need
🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!
mdabros/SharpLearning
Machine learning for C# .Net
ledell/useR-machine-learning-tutorial
useR! 2016 Tutorial: Machine Learning Algorithmic Deep Dive http://user2016.org/tutorials/10.html