OpenML-Python: an extensible Python API for OpenML

OpenML-Python: an extensible Python API for OpenML

6 November 2019

Matthias Feurer

Jan N. van Rijn

Pieter Gijsbers

Neeratyoy Mallik

Andreas Müller

Joaquin Vanschoren

Papers citing "OpenML-Python: an extensible Python API for OpenML"

19 / 19 papers shown

Title
PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework Abhineet Agarwal Michael Xiao Rebecca L. Barter Omer Ronen Boyu Fan Bin Yu 34 0 0 13 May 2025
ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data Valentin Margraf Marcel Wever Sandra Gilhuber Gabriel Marques Tavares Thomas Seidl Eyke Hüllermeier 44 0 0 25 Jun 2024
A systematic study comparing hyperparameter optimization engines on tabular data Balazs Kegl 23 1 0 27 Nov 2023
Meta-learning of semi-supervised learning from tasks with heterogeneous attribute spaces Tomoharu Iwata Atsutoshi Kumagai 26 2 0 09 Nov 2023
CAST: Cluster-Aware Self-Training for Tabular Data Minwook Kim Juseong Kim Kibeom Kim Giltae Song 33 0 0 10 Oct 2023
Model Share AI: An Integrated Toolkit for Collaborative Machine Learning Model Development, Provenance Tracking, and Deployment in Python Heinrich Peters Michael Parrott 21 0 0 27 Sep 2023
OpenBox: A Python Toolkit for Generalized Black-box Optimization Huaijun Jiang Yu Shen Yang Li Beicheng Xu Sixian Du Wentao Zhang Ce Zhang Bin Cui 38 4 0 26 Apr 2023
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value Yongchan Kwon James Zou TDI FedML 39 35 0 16 Apr 2023
Conceptual Views on Tree Ensemble Classifiers Tom Hanika Johannes Hirth 40 4 0 10 Feb 2023
Mind the Gap: Measuring Generalization Performance Across Multiple Objectives Matthias Feurer Katharina Eggensperger Eddie Bergman Florian Pfisterer B. Bischl Frank Hutter 51 5 0 08 Dec 2022
Boosted Off-Policy Learning Ben London Levi Lu Ted Sandler Thorsten Joachims OffRL 46 4 0 01 Aug 2022
Data structure > labels? Unsupervised heuristics for SVM hyperparameter estimation M. Cholewa M. Romaszewski P. Głomb 26 0 0 03 Nov 2021
abess: A Fast Best Subset Selection Library in Python and R Jin Zhu Xueqin Wang Liyuan Hu Junhao Huang Kangkang Jiang Yanhang Zhang Shiyun Lin Junxian Zhu 21 22 0 19 Oct 2021
SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption Dara Bahri Heinrich Jiang Yi Tay Donald Metzler SSL 19 163 0 29 Jun 2021
Unbiased Gradient Estimation for Distributionally Robust Learning Soumyadip Ghosh M. Squillante OOD 21 7 0 22 Dec 2020
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning Matthias Feurer Katharina Eggensperger Stefan Falkner Marius Lindauer Frank Hutter 35 266 0 08 Jul 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 30 2,652 0 02 May 2020
Confident Learning: Estimating Uncertainty in Dataset Labels Curtis G. Northcutt Lu Jiang Isaac L. Chuang NoLa 38 674 0 31 Oct 2019
OpenML Benchmarking Suites B. Bischl Giuseppe Casalicchio Matthias Feurer Pieter Gijsbers Frank Hutter Michel Lang R. G. Mantovani Jan N. van Rijn Joaquin Vanschoren VLM ELM 41 151 0 11 Aug 2017