ds_basic()
A basic datasource (DS)
ds_generalization()
A datasource (DS) that allows training and testing on different but related labels
fp_select_k_features()
A feature preprocessor (FP) that reduces data to the k most selective features
fp_zscore()
A feature preprocessor (FP) that z-score normalizes the data
cl_max_correlation()
A maximum correlation coefficient classifier (CL)
cl_poisson_naive_bayes()
A Poisson Naive Bayes classifier (CL)
cl_svm()
A support vector machine classifier (CL)
cv_standard()
The standard cross-validator (CV)
rm_main_results()
A result metric (RM) that calculates main decoding accuracy measures
rm_confusion_matrix()
A result metric (RM) that calculates confusion matrices
plot(<rm_main_results>)
A plot function for the rm_main_results object
plot(<rm_confusion_matrix>)
A plot function for the rm_confusion_matrix object
log_save_results()
Saves the DECODING_RESULTS and logs the parameters used in the analysis
log_check_results_already_exist()
A function that checks if a decoding analysis has already been run
log_load_results_from_result_name()
A function that loads DECODING_RESULTS based on the result_name
log_load_results_from_params()
A function that loads DECODING_RESULTS based on decoding_parameters
create_binned_data()
Convert data from raster format to binned format
convert_matlab_raster_data()
Convert raster data in MATLAB to R
get_num_label_repetitions()
Get the number of trial repetitions for a given label