Topic: "binomial-logistic-regression"
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
Language: Python - Size: 6.39 MB - Last synced at: 2 days ago - Pushed at: almost 7 years ago - Stars: 2 - Forks: 1
Asmagithu/Prediction-with-Binomial-Logistic-Regression-19th-November
This repo includes Prediction with Binomial Logistic Regression.
Size: 1.36 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
T-Obuchi/AcceleratedCVonMLR_matlab
This MATLAB 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. Python version: https://github.com/T-Obuchi/AcceleratedCVonMLR_python
Language: MATLAB - Size: 34.2 KB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 0 - Forks: 1