Function reference • NeuroDecodeR

Datasources
`ds_basic()`	A basic datasource (DS)
`ds_generalization()`	A datasource (DS) that allows training and testing on different but related labels
Feature preprocessors
`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
Classifiers
`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)
Cross-validators
`cv_standard()`	The standard cross-validator (CV)
`run_decoding(<cv_standard>)`	A cross-validator (CV) method to run a decoding analysis
`get_parameters(<cv_standard>)`	Get parameters of an NeuroDecodeR object
Result Metrics
`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 functions
`plot(<raster_data>)`	A plot function for data in raster format
`plot(<label_repetition>)`	A plot function for label_repetition object
`plot(<rm_main_results>)`	A plot function for the rm_main_results object
`plot_main_results()`	A plot function to plot multiple rm_main_results
`plot(<rm_confusion_matrix>)`	A plot function for the rm_confusion_matrix object
Save and log results
`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
Tools
`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 sites have at least k trials of each label level
`get_siteIDs_with_k_label_repetitions()`	Get the sitesIDs that have at least k trials for all label level
`get_num_label_repetitions_each_site()`	Get the number of trial repetitions for a given label for each site
`read_raster_data()`	Read a csv, rda, rds or mat file in raster format
`test_valid_raster_format()`	Tests if a data frame is in valid raster format

Reference

Datasources

Feature preprocessors

Classifiers

Cross-validators

Result Metrics

Plot functions

Save and log results

Tools