Changelog¶
CoSMoMVPA changelog¶
1.1.0 (2016-12-06)
Fixed
Major Fix issue in cosmo montecarlo cluster stat, which returned z-scores corresponding than one-tailed instead of two-tailed probabilities, doubling the Type I error rate.
When using GNU Octave, let cosmo check external deal properly with packages that are installed but not loaded.
Changed behaviour
In cosmo crossvalidate, the first output contains (for each sample) a prediction for each fold, rather than one single prediction computed by cosmo winner indices. (Unchanged is that cosmo crossvalidation measure returns, by default, a single prediction per sample).
Deprecated
In cosmo crossvalidation measure, the “predictions” and “raw” output options are deprecated; use “winner_predictions” instead.
cosmo dataset slice fa and cosmo dataset slice fa will be removed in the future; use cosmo slice instead.
cosmo dim slice will be removed in the future; use cosmo slice and cosmo dim prune instead.
cosmo meta feature selection classifier will be removed in the future; use cosmo classify meta feature selection instead.
Removed
in cosmo crossvalidation measure, the “accuracy_by_chunk” output option has been removed. Use “fold_predictions” to get predictions for each fold.
in cosmo naive bayes classifier searchlight, the “predictions” output option has been removed. Use “winner_predictions” instead.
New features
cosmo meeg dataset and cosmo map2meeg provide input/output support for EEGLAB datasets with study structure, and for FieldTrip datasets with “subj” as the first dimension in dimord.
cosmo montecarlo cluster stat and cosmo searchlight support parallellization over multiple CPU cores/threads using the “nproc” parameter.
New function cosmo independent samples partitioner for MEEG datasets where samples can be assumed to be independent.
New function cosmo randperm with optional seed.
New functions for parallel computations on the Matlab and Octave platform, cosmo parallel get nproc available and cosmo parcellfun.
New functions cosmo map pca and cosmo pca for Principal Component Analysis (PCA), and support for PCA in cosmo crossvalidate and cosmo crossvalidation measure.
Added Changelog
Contributors
Tijl Grootswagers
Acknowledgements
Christoph Braun
Tijl Grootswagers
Thomas Hinault
Maria Montchal
Daria Proklova
Joscha Schmiedt
Jo Taylor
Lara Todorova
Raffaele Tucciarelli
1.0.0 (2016-07-22)
First public release.