Skip to main content

Package that provides scikit-learn compatible cross validators with stratification for multilabel data

Project description

This iterative-stratification project offers implementations of MultilabelStratifiedKFold, MultilabelRepeatedStratifiedKFold, and MultilabelStratifiedShuffleSplit with a base algorithm for stratifying multilabel data described in the following paper: Sechidis K., Tsoumakas G., Vlahavas I. (2011) On the Stratification of Multi-Label Data. In: Gunopulos D., Hofmann T., Malerba D., Vazirgiannis M. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2011. Lecture Notes in Computer Science, vol 6913. Springer, Berlin, Heidelberg.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

iterative-stratification-0.1.3.tar.gz (5.8 kB view details)

Uploaded Source

File details

Details for the file iterative-stratification-0.1.3.tar.gz.

File metadata

File hashes

Hashes for iterative-stratification-0.1.3.tar.gz
Algorithm Hash digest
SHA256 6e8a883a73103050dfef1cdc002b444cbbfcd5479d64a4fcd6c07aae2aabce14
MD5 5f26290c3882d0f851c80a376e811d07
BLAKE2b-256 e270490089e024cd8b902af86744335972d2a9d2ad35cdbfc95ef0d8e07e3f2d

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page