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GitHub / T-Obuchi / AcceleratedCVonMLR_python

This Python package enables to efficiently compute leave-one-out cross validation error for multinomial logistic regression with elastic net (L1 and L2) penalty. The computation is based on an analytical approximation, which enables to avoid re-optimization and to reduce much computational time. MATLAB version: https://github.com/T-Obuchi/AcceleratedCVonMLR_matlab

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/T-Obuchi%2FAcceleratedCVonMLR_python

Stars: 2
Forks: 1
Open issues: 0

License: gpl-3.0
Language: Python
Size: 6.39 MB
Dependencies parsed at: Pending

Created at: over 7 years ago
Updated at: over 2 years ago
Pushed at: almost 7 years ago
Last synced at: 4 days ago

Topics: binomial-logistic-regression, multinomial-logistic-regression, python

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