Awesome Decision Tree PapersA collection of research papers on decision, classification and regression trees with implementations.
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stackgbm🌳 Stacked Gradient Boosting Machines
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HyperGBMA full pipeline AutoML tool for tabular data
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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.
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TpotA Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
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Mljar SupervisedAutomated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀
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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
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Machine-Learning-ModelsIn This repository I made some simple to complex methods in machine learning. Here I try to build template style code.
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Auto ml[UNMAINTAINED] Automated machine learning for analytics & production
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scorubyRuby Scoring API for PMML
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cheapmlMachine Learning algorithms coded from scratch
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Apartment-Interest-PredictionPredict people interest in renting specific NYC apartments. The challenge combines structured data, geolocalization, time data, free text and images.
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handson-ml도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.
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yggdrasil-decision-forestsA collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.
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fast retrainingShow how to perform fast retraining with LightGBM in different business cases
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Benchm MlA 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.).
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Machine Learning In RWorkshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
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datascienvdatascienv is package that helps you to setup your environment in single line of code with all dependency and it is also include pyforest that provide single line of import all required ml libraries
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Tensorflow Ml Nlp텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)
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mlforecastScalable machine 🤖 learning for time series forecasting.
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Kaggle-Competition-SberbankTop 1% rankings (22/3270) code sharing for Kaggle competition Sberbank Russian Housing Market: https://www.kaggle.com/c/sberbank-russian-housing-market
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recsys2019The complete code and notebooks used for the ACM Recommender Systems Challenge 2019
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HumanOrRobota solution for competition of kaggle `Human or Robot`
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Leavespure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks
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XgboostScalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
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Hyperparameter hunterEasy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
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H2o 3H2O 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.
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Arch-Data-ScienceArchlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision
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DrishtiReal time eye tracking for embedded and mobile devices.
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OpenscoringREST web service for the true real-time scoring (<1 ms) of Scikit-Learn, R and Apache Spark models
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RobustTrees[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples
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NyokaNyoka is a Python library to export ML/DL models into PMML (PMML 4.4.1 Standard).
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BenchmarksComparison tools
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MarsMars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
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Dc Hi guides[Data Castle 算法竞赛] 精品旅行服务成单预测 final rank 11
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M2cgenTransform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
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Gbm PerfPerformance of various open source GBM implementations
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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)
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MlboxMLBox is a powerful Automated Machine Learning python library.
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Eli5A library for debugging/inspecting machine learning classifiers and explaining their predictions
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DtreevizA python library for decision tree visualization and model interpretation.
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SentimentAnalysis(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset
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arboretoA scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.
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MLDay18Material from "Random Forests and Gradient Boosting Machines in R" presented at Machine Learning Day '18
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AutoTabularAutomatic machine learning for tabular data. ⚡🔥⚡
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data-science-popular-algorithmsData Science algorithms and topics that you must know. (Newly Designed) Recommender Systems, Decision Trees, K-Means, LDA, RFM-Segmentation, XGBoost in Python, R, and Scala.
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