Title: SciKit-Learn Laboratory (SKLL) 0.26.0

Type Software Dan Blanchard, Michael Heilman, Nitin Madnani, Nils Murrugarra Llerena, Aoife Cahill (2014): SciKit-Learn Laboratory (SKLL) 0.26.0. Zenodo. Software. https://zenodo.org/record/10849

Authors: Dan Blanchard (Educational Testing Service) ; Michael Heilman (Educational Testing Service) ; Nitin Madnani (Educational Testing Service) ; Nils Murrugarra Llerena (University of Pittsburgh) ; Aoife Cahill (Educational Testing Service) ;

Links

• Item record in Zenodo
• Digital object URL

Summary

Added AdaBoost and KNeighbors classifiers and regressors (finally closing #7). Added support for kernel approximation samplers. (Thanks @nineil) All linear models are now supported by print_model_weights (issue #119). Added f1_score_weighted metric so that weighted F1 will be calculated even for binary classification tasks. Modified f1_score_micro and f1_score_macro to also always return average for binary classification tasks (instead of previous behavior where only performance on positive class was returned).

More information

• DOI: 10.5281/zenodo.10849

Subjects

• machine learning, Python

Dates

• Publication date: 2014
• Issued: July 11, 2014

Rights

• http://www.opensource.org/licenses/bsd-license.php BSD licenses (New and Simplified)
• info:eu-repo/semantics/openAccess Open Access

Format

electronic resource

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