Test symmetries with sklearn decision tree models
Setup
Begin from an environment with a recent version of python 3.
source setup.sh
Leave the environment with deactivate. Clean up fully by removing env/.
Run examples
make
Begin from an environment with a recent version of python 3.
source setup.sh
Leave the environment with deactivate. Clean up fully by removing env/.
make
Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
Data Efficient Decision Making
MBTR is a python package for multivariate boosted tree regressors trained in parameter space.
implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map, play blackjack game and robot in grid world and evaluate reward for it
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized
Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco
Auto_TS: Auto_TimeSeries Automatically build multiple Time Series models using a Single Line of Code. Now updated with Dask. Auto_timeseries is a comp
First version to go on Zenodo 🤖 second major version ♊
Source code(tar.gz)MPI for Python Overview Welcome to MPI for Python. This package provides Python bindings for the Message Passing Interface (MPI) standard. It is imple
vecstack Python package for stacking (stacked generalization) featuring lightweight functional API and fully compatible scikit-learn API Convenient wa
Advanced-Machine-Learning This repository contains the code for the project Real
InterpretML - Alpha Release In the beginning machines learned in darkness, and data scientists struggled in the void to explain them. Let there be lig
AutoML Service Deploy automated machine learning (AutoML) as a service using Flask, for both pipeline training and pipeline serving. The framework imp
eXtreme Gradient Boosting Community | Documentation | Resources | Contributors | Release Notes XGBoost is an optimized distributed gradient boosting l
AI Fairness 360 (AIF360) The AI Fairness 360 toolkit is an extensible open-source library containg techniques developed by the research community to h
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learn
AutoTS AutoTS is a time series package for Python designed for rapidly deploying high-accuracy forecasts at scale. There are dozens of forecasting mod
🌄 Scalecast: Dynamic Forecasting at Scale About This package uses a scaleable forecasting approach in Python with common scikit-learn and statsmodels
Python-Fast-Raytracer A basic Ray Tracer that exploits numpy arrays and functions to work fast. The code is written keeping as much readability as pos
Machine Learning Videos This is a collection of recorded talks at machine learning conferences, workshops, seminars, summer schools, and miscellaneous
pm-prophet Pymc3-based universal time series prediction and decomposition library (inspired by Facebook Prophet). However, while Faceook prophet is a
mlflow-azurite-postgres docker This is a MLFLow image which works with a postgres DB and a local Azure Blob Storage Instance (Azurite). This image is
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo
Multiple-Linear-Regression-master - A python program to implement Multiple Linear Regression using the LinearRegression class from sklearn.linear model library
CVXPY The CVXPY documentation is at cvxpy.org. We are building a CVXPY community on Discord. Join the conversation! For issues and long-form discussio
timemachines Autonomous, univariate, k-step ahead time-series forecasting functions assigned Elo ratings You can: Use some of the functionality of a s
This library was developed in order to facilitate rapid prototyping in Python of predictive machine-learning models using longitudinal medical data from an OMOP CDM-standard database.
LibRerank LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRer