an efficient gradient-based model selection algorithm for MLSSVR
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Updated
Apr 21, 2018 - MATLAB
an efficient gradient-based model selection algorithm for MLSSVR
Python cross-validation package with k-fold, leave-one-out and leave-one-subject-out
A Python implementation of feature selection algorithms using k-Nearest Neighbor classification. This project implements three different search strategies for finding optimal feature subsets: Forward Selection, Backward Elimination, and Simulated Annealing.
A function in Matlab that performs leave-one-out cross validation of the previously created regression model. CV function performs cross-validation for linear regression, and CVbin for binomial regression
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