TITLE: PMLB v1.0: An open source dataset collection for benchmarking machine learning methods 

ABSTRACT: Motivation: Novel machine learning and statistical modeling studies rely on
standardized comparisons to existing methods using well-studied benchmark
datasets. Few tools exist that provide rapid access to many of these datasets
through a standardized, user-friendly interface that integrates well with
popular data science workflows.
  Results: This release of PMLB provides the largest collection of diverse,
public benchmark datasets for evaluating new machine learning and data science
methods aggregated in one location. v1.0 introduces a number of critical
improvements developed following discussions with the open-source community.
  Availability: PMLB is available at https://github.com/EpistasisLab/pmlb.
Python and R interfaces for PMLB can be installed through the Python Package
Index and Comprehensive R Archive Network, respectively.
Motivation: Novel machine learning and statistical modeling studies rely on
standardized comparisons to existing methods using well-studied benchmark
datasets. Few tools exist that provide rapid access to many of these datasets
through a standardized, user-friendly interface that integrates well with
popular data science workflows.
  Results: This release of PMLB provides the largest collection of diverse,
public benchmark datasets for evaluating new machine learning and data science
methods aggregated in one location. v1.0 introduces a number of critical
improvements developed following discussions with the open-source community.
  Availability: PMLB is available at https://github.com/EpistasisLab/pmlb.
Python and R interfaces for PMLB can be installed through the Python Package
Index and Comprehensive R Archive Network, respectively.
PMLB v1.0: An open source dataset collection for benchmarking machine learning methods
http://arxiv.org/abs/2012.00058v3