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)rpforest rpforest is a Python library for approximate nearest neighbours search: finding points in a high-dimensional space that are close to a given
Federal University of Rio Grande do Norte Technology Center Department of Computer Engineering and Automation Machine Learning Based Systems Design Re
kNN-vs-RFR My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data In many areas, rental bikes have been launched to
Model Factory Machine learning today is powering many businesses today, e.g., search engine, e-commerce, news or feed recommendation. Training high qu
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics
InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De
xarray-einstats Stats, linear algebra and einops for xarray ⚠️ Caution: This project is still in a very early development stage Installation To instal
Somoclu Somoclu is a massively parallel implementation of self-organizing maps. It exploits multicore CPUs, it is able to rely on MPI for distributing
Object Relation Transformer This is a PyTorch implementation of the Object Relation Transformer published in NeurIPS 2019. You can find the paper here
Graph-based CTR prediction This is a repository designed for graph-based CTR prediction methods, it includes our graph-based CTR prediction methods: F
BigDL: Distributed Deep Learning on Apache Spark What is BigDL? BigDL is a distributed deep learning library for Apache Spark; with BigDL, users can w
Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage
pytools is an open source library containing general machine learning and visualisation utilities for reuse, including: Basic tools for API developmen
This project has Classification and Clustering done Via kNN and K-Means respectfully. It later tests its efficiency via F1/accuracy/recall/precision for kNN and Davies-Bouldin Index for Clustering. T
AutoML Service Deploy automated machine learning (AutoML) as a service using Flask, for both pipeline training and pipeline serving. The framework imp
A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.
You can perform Land Cover Classification on Satellite Images using Random Forest and visualize the result using Earthpy package. Make sure to install the required packages and such as
monolish is a linear equation solver library that monolithically fuses variable data type, matrix structures, matrix data format, vendor specific data transfer APIs, and vendor specific numerical alg
ml4ir: Machine Learning for Information Retrieval | changelog Quickstart → ml4ir Read the Docs | ml4ir pypi | python ReadMe ml4ir is an open source li
High Performance toolbox for Extreme Learning Machines. Extreme learning machines (ELM) are a particular kind of Artificial Neural Networks, which sol