Description: The leave-one-out cross-validation scheme is a method for estimating the average generalization error. When calling [Eloo, H] = loo (NetDef, W1, W2, PHI, Y, trparms) with trparms (1)> 0, the network will be retrained a maximum of trparms (1) iterations for each input-output pair in the data set, starting from the initial weights (W1, W2). If trparms (1) = 0 an approximation to the loo-estimate based on linear unlearning is produced. This is in general less accurate, but is much faster to calculate.
- [svm_toolbox] - SVM Toolbox, which contains MATLAB demo
- [svm_v0.01beta.tar] - New in this version : Support for multi-
- [leaveoneout] - Leave-one of the matlab source code, it
- [gcv] - GCV Generalized cross-validation. Genera
- [fpe] - This function calculates Akaike s final
- [SLOO-MPS-SVM] - Using SLOO-MPS for tuning multiple param
File list (Check if you may need any files):
loo.m
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