Hi TDT experts,
I tried the decoding tutorial to set up a cross-classification analysis (adding z scaling and embedded RFE) with the default libsvm classifier, and it all worked fine. However, when I changed from ‘libsvm’ to cfg.decoding.software = ‘lda’; I got the below error message. Presumably I need to change some default parameters to make them suitable for LDA?
Dot indexing is not supported for variables of this type.
Error in ldatrain (line 51) switch lower(param.shrinkage)
Error in lda_train (line 9) model = ldatrain(labels_train,data_train,cfg.decoding.train.classification.model_parameters);
Error in RFE (line 34) model = feval(cfg.feature_selection.decoding.fhandle_train,labels_train,data_train(:,ranks),cfg.feature_selection);
Error in feature_selection_embedded (line 80)
ranks = feval(cfg.feature_selection.embedded_func,cfg,ranks,final_n_vox,iteration,data_scaled,labels);
Error in decoding_feature_selection (line 235)
[fs_index,n_vox_steps,output] = feature_selection_embedded(cfg,labels,data_scaled,n_vox,nested_n_vox,i_train);
Error in decoding (line 474)
[fs_index,fs_results,previous_fs_data] = decoding_feature_selection(cfg,fs_data);
Error in TDT_ROI (line 115)
[results, cfg] = decoding(cfg);