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)ml4ir: Machine Learning for Information Retrieval | changelog Quickstart → ml4ir Read the Docs | ml4ir pypi | python ReadMe ml4ir is an open source li
xeasy-ml 1. What is xeasy-ml Xeasy-ml is a packaged machine learning framework. It allows a beginner to quickly build a machine learning model and use
auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here
MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th
KXY: A Seemless API to 10x The Productivity of Machine Learning Engineers Documentation https://www.kxy.ai/reference/ Installation From PyPi: pip inst
WAGMA-SGD is a decentralized asynchronous SGD based on wait-avoiding group model averaging. The synchronization is relaxed by making the collectives externally-triggerable, namely, a collective can b
Case studies with Bayesian methods
Tools for mathematical optimization region
Scikit-Pipes Scikit-Learn useful pre-defined Pipelines Hub Usage: Install scikit-pipes It's advised to install sklearn-genetic using a virtual env, in
A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.
High Performance toolbox for Extreme Learning Machines. Extreme learning machines (ELM) are a particular kind of Artificial Neural Networks, which sol
Traingenerator 🧙 A web app to generate template code for machine learning ✨ 🎉 Traingenerator is now live! 🎉
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.
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
BartPy Introduction BartPy is a pure python implementation of the Bayesian additive regressions trees model of Chipman et al [1]. Reasons to use BART
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in
scikit-fem is a lightweight Python 3.7+ library for performing finite element assembly. Its main purpose is the transformation of bilinear forms into sparse matrices and linear forms into vectors.
Binary Classification Problem with Machine Learning Solving Approach: 1) Ultimate Goal of the Assignment: This assignment is about solving a binary cl
Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o
fourier-bayesian-sv-estimation Fourier-Bayesian estimation of stochastic volatility models Code used to run the numerical examples of "Bayesian Approa