Multi Target Regression Python Packages

mlrl-boomer

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-Output Rules

mlrl-common

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-Output Rules

mlrl-seco

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-Output Rules

xgboostlss

An extension of XGBoost to probabilistic modelling

mlrl-util

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-Output Rules

mlrl-testbed

Provides utilities for the training and evaluation of machine learning algorithms

mlrl-testbed-sklearn

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-Output Rules

mlrl-testbed-arff

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-Output Rules

scikit-physlearn

A machine learning library for regression, which implements a new formulation of gradient boosting.

mlrl-testbed-slurm

Adds support for the Slurm Workload Manager to the package "mlrl-testbed"

amorf

A Multi-Output Regression Framework in Python