Orange3🍊 📊 💡 Orange: Interactive data analysis
ChefboostA Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python
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!
LightgbmA 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.
Machine learningEstudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
Machine Learning ModelsDecision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means
Machine Learning In RWorkshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
Dat8General Assembly's 2015 Data Science course in Washington, DC
Predicting real estate prices using scikit LearnPredicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)
SporfThis is the implementation of Sparse Projection Oblique Randomer Forest
ExploreR package that makes basic data exploration radically simple (interactive data exploration, reproducible data science)
C4.5A python implementation of C4.5 algorithm by R. Quinlan
TreeheatrHeatmap-integrated Decision Tree Visualizations
RgfHome 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.
Fuku MlSimple machine learning library / 簡單易用的機器學習套件
Leavespure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks
DtreevizA python library for decision tree visualization and model interpretation.
linear-treeA python library to build Model Trees with Linear Models at the leaves.
cortana-intelligence-customer360This repository contains instructions and code to deploy a customer 360 profile solution on Azure stack using the Cortana Intelligence Suite.
aifadAIFAD - Automated Induction of Functions over Algebraic Data Types
df-dn-paperConceptual & empirical comparisons between decision forests & deep networks
Pac-ManEvolutionary Pac-Man bots using Grammatical Evolution and Multi-objective Optimization. Cool GUI included (Undergraduate Thesis)
lleavesCompiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.
MLDay18Material from "Random Forests and Gradient Boosting Machines in R" presented at Machine Learning Day '18
QuantumForestFast Differentiable Forest lib with the advantages of both decision trees and neural networks
IPL-ML-2018Predicting IPL match results. https://kuharan.github.io/IPL-ML-2018/
Amazon-Fine-Food-ReviewMachine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review
Encoder-ForesteForest: Reversible mapping between high-dimensional data and path rule identifiers using trees embedding
GROOT[ICML 2021] A fast algorithm for fitting robust decision trees. http://proceedings.mlr.press/v139/vos21a.html
yggdrasil-decision-forestsA collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.
supervised-machine-learningThis repo contains regression and classification projects. Examples: development of predictive models for comments on social media websites; building classifiers to predict outcomes in sports competitions; churn analysis; prediction of clicks on online ads; analysis of the opioids crisis and an analysis of retail store expansion strategies using…
ProtoTreeProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021
ecPoint-CalibrateInteractive GUI (developed in Python) for calibration and conditional verification of numerical weather prediction model outputs.
rfvisA tool for visualizing the structure and performance of Random Forests 🌳
RobustTrees[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples
multi-imbalancePython package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/
interpretable-mlTechniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.