Creative Commons CCZero (CC0-1.0), Open Data Commons Public Domain Dedication and Licence (PDDL-1.0)
Health, Science and Technology
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* Please note that the classification is taken from the original source
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality metrics (e.g. accuracy, precision, area under ROC curve, etc.) for classification, feature selection or clustering algorithms. This repository was inspired by an increasing need in machine learning / bioinformatics communities for a collection of microarray classification problems that could be used by different researches. This way many different classification or feature selection techniques can finally be compared to eachother on the same set of problems.
Disclaimer: This data is provided by a third party. The DIH identifying this data has no responsibility for its content. Please check the provided link to the data for license terms and potential usage restrictions. In case personal data is included in the dataset, the third party who provides the dataset is the data controller of such personal data. Please note that if you use the datasets for your own purposes, you become an independent data controller and are solely responsible for your compliance with relevant data protection laws relating to the processing and security of personal data, with particular reference, but not limited to, the provisions of the General Data Protection Regulation (GDPR), as applicable to the personal data included in the data.
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