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
Test symmetries with sklearn decision tree models
Overview
You might also like...
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models
Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class
482 Nov 19, 2022
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
6.9k Jan 5, 2023
Data Efficient Decision Making
Data Efficient Decision Making
197 Jan 6, 2023
MBTR is a python package for multivariate boosted tree regressors trained in parameter space.
MBTR is a python package for multivariate boosted tree regressors trained in parameter space.
61 Dec 19, 2022
Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )
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
1 Jan 19, 2022
A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
1.4k Jan 6, 2023
![[HELP REQUESTED] Generalized Additive Models in Python](https://github.com/dswah/pyGAM/raw/master/imgs/pygam_tensor.png)
[HELP REQUESTED] Generalized Additive Models in Python
pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized
747 Jan 5, 2023
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco
129 Dec 24, 2022
Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.
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
519 Jan 3, 2023
Releases(zenodo-1)
-
zenodo-1(Jul 19, 2022)
First version to go on Zenodo 🤖 second major version ♊
Source code(tar.gz)
Source code(zip)
🤖 ⚡ scikit-learn tips
🤖 ⚡ scikit-learn tips New tips are posted on LinkedIn, Twitter, and Facebook. 👉 Sign up to receive 2 video tips by email every week! 👈 List of all
1.6k Jan 03, 2023
Made in collaboration with Chris George for Art + ML Spring 2019.
Deepdream Eyes Made in collaboration with Chris George for Art + ML Spring 2019.
1 Jan 12, 2022
Module for statistical learning, with a particular emphasis on time-dependent modelling
Operating system Build Status Linux/Mac Windows tick tick is a Python 3 module for statistical learning, with a particular emphasis on time-dependent
410 Dec 14, 2022
Adaptive: parallel active learning of mathematical functions
adaptive Adaptive: parallel active learning of mathematical functions. adaptive is an open-source Python library designed to make adaptive parallel fu
741 Dec 27, 2022
Transform ML models into a native code with zero dependencies
m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code
2.3k Jan 03, 2023
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber
124 Dec 28, 2022
A 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.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
14.5k Jan 07, 2023
Predict profitability of trades based on indicator buy / sell signals
Predict profitability of trades based on indicator buy / sell signals Trade profitability analysis for trades based on various indicators signals: MAC
1 Dec 15, 2021
AtsPy: Automated Time Series Models in Python (by @firmai)
Automated Time Series Models in Python (AtsPy) SSRN Report Easily develop state of the art time series models to forecast univariate data series. Simp
465 Jan 02, 2023
A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.
A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.
80 Dec 12, 2022
A modular active learning framework for Python
Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe
1.9k Dec 31, 2022
A python library for easy manipulation and forecasting of time series.
Time Series Made Easy in Python darts is a python library for easy manipulation and forecasting of time series. It contains a variety of models, from
5.2k Jan 04, 2023
A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and motion planning
pybullet-planning (previously ss-pybullet) A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and
260 Dec 27, 2022
This project impelemented for midterm of the Machine Learning #Zoomcamp #Alexey Grigorev
MLProject_01 This project impelemented for midterm of the Machine Learning #Zoomcamp #Alexey Grigorev Context Dataset English question data set file F
1 Dec 18, 2021
Python ML pipeline that showcases mltrace functionality.
mltrace tutorial Date: October 2021 This tutorial builds a training and testing pipeline for a toy ML prediction problem: to predict whether a passeng
28 Nov 09, 2022
Credit Card Fraud Detection, used the credit card fraud dataset from Kaggle
Credit Card Fraud Detection, used the credit card fraud dataset from Kaggle
1 Feb 04, 2022
MLR - Machine Learning Research
Machine Learning Research 1. Project Topic 1.1. Exsiting research Benmark: https://paperswithcode.com/sota ACL anthology for NLP papers: http://www.ac
69 Oct 20, 2022
This is a Machine Learning model which predicts the presence of Diabetes in Patients
Diabetes Disease Prediction This is a machine Learning mode which tries to determine if a person has a diabetes or not. Data The dataset is in comma s
4 Mar 16, 2022
Time series changepoint detection
changepy Changepoint detection in time series in pure python Install pip install changepy Examples from changepy import pelt from cha
92 Nov 08, 2022
Data Efficient Decision Making
Data Efficient Decision Making
197 Jan 06, 2023