Reverse Dependencies of openml

The following projects have a declared dependency on openml:

• AI-Education-Tools — AI Education Tools for Teaching
• alpbench — Active Learning Pipelines Benchmark
• assembled — Efficiently Benchmarking Ensembles in AutoML
• at-ml — A Toolbox for Adaptive Testing on Machine Learning Experiments
• autogluon.extra — AutoML for Text, Image, and Tabular Data
• autogluon.mxnet — AutoML for Text, Image, and Tabular Data
• autopocket — Automated Machine Learning project for financial data analysis.
• autoPyTorch — Auto-PyTorch searches neural architectures using smac
• beexai — BEExAI: Benchmark to Evaluate Explainable AI
• caafe — Context-Aware Automated Feature Engineering (CAAFE) is an automated machine learning tool that uses large language models for feature engineering in tabular datasets. It generates Python code for new features along with explanations for their utility, enhancing interpretability.
• croissant-rdf — Tools for working with RDF from Croissant JSON-LD resources.
• d3m — project
• datacleanbot — automated data cleaning tool
• DatasetsEvaluator — A tool to automate collecting and testing against datasets on openml.org
• dehb — Evolutionary Hyperband for Scalable, Robust and Efficient Hyperparameter Optimization
• df-analyze — Add your description here
• dirty_cat — Machine learning with dirty categories.
• dragon-autodl — Implementation of the algorithmic framework from <An algorithmic framework for the optimization of deep neural networks architectures and hyperparameters>
• dswizard — DataScience Wizard for automatic assembly of machine learning pipelines
• edgaro — Explainable imbalanceD learninG compARatOr
• FLAML — A fast library for automated machine learning and tuning
• futureframe — Accelerate your data science workflow from months to days with foundation models for tabular data.
• gamlet — Framework for meta-optimisation in AutoML tasks
• genens — A genetic AutoML system for ensemble methods
• giotto-deep — Toolbox for Deep Learning and Topological Data Analysis.
• giotto-tda — Toolbox for Machine Learning using Topological Data Analysis.
• giotto-tda-nightly — Toolbox for Machine Learning using Topological Data Analysis.
• itabpfn — Interface for using interfeature TabPFN and library to train TabPFN'
• itabpfn-l1 — Interface for using interfeature TabPFN and library to train TabPFN'
• itabpfn2 — Interface for using interfeature TabPFN and library to train TabPFN'
• ixai — Explainable Artificial Intelligence for dynamic and Incremental models.
• lucid-dl — Lumerico's Comprehensive Interface for Deep Learning
• meta-ml — MetaRL-based Estimator using Task-encodings for AutoML
• MetaFEDOT — Framework for meta-optimisation in AutoML tasks
• mlcompare — Quickly compare machine learning models across libraries and datasets.
• mlgauge — Library to compare machine learning methods across datasets
• mlpro-int-openml — MLPro: Integration OpenML
• oboe — An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.
• openml-keras — Keras extension for Openml python API
• openml-mxnet — MXNet extension for Openml python API
• openml-onnx — Onnx extension for Openml python API
• openml-pytorch — Pytorch extension for OpenML
• openml-tensorflow — Tensorflow extension for Openml python API
• origami-ml — An ML classifier model to make predictions from semi-structured data.
• powerlift — Interactive Benchmarking for Machine Learning.
• prevision-quantum-nn — Prevision Automating Quantum Neural Networks Applications
• pycurator — Collect data from popular data repositories with ease.
• pyPDPPartitioner — A python implementation of 'Explaining Hyperparameter Optimization via Partial Dependence Plots' by Moosbauer et al.
• pytabkit — ML models + benchmark for tabular data classification and regression
• quask — A software framework to speed up the research in quantum machine learning
• qxmt — QXMT is a experiment management tool for quantum computing and quantum machine learning.
• shap-bootstrap — Software package for implementing shap-bootstrapping
• SoEasyData — 快速获取数据的简洁程序库
• spectralexplain — Spectral Explainer: Scalable Feature Interaction Attribution
• sundar-gap-stat — Sundar-Tibshirani Gap Statistic for cluster analysis
• TabPFNbaseline — Interface for using interfeature TabPFN and library to train TabPFN'
• tamu-d3m — project
• transtab — A flexible tabular prediction model that handles variable-column input tables.
• validating-models — Supporting Explainable AI on Semantic Constraint Validation
• ws-benchmark — a weak supervision learning benchmark
• wsmf — Package with encoder-based approaches to warm-starting Bayesian Hyperparameter Optimization.