 CNN1D_data_prepration | CNN1D_data_prepration(ml_data) converts train and test inputs to a 4D array |
| bmech_compute_features | bmech_compute_features(fld, ch, method) extracts basic statistical features from line data |
| bmech_events2table | BMECH_EVENTS2TABLE(fld,ch,event,subjects,Conditions) extracts local events to |
| bmech_line2table | BMECH_ZOO2TABLE (fld,ch,subjects,conditions) extracts channel line data |
| char2num | y=char2num(y) support function for machine learning module, converts |
| emptytable | |
| emptytable_data | table_event=emptytable_data(fl,ch) creates emptytable |
| ml_model_parameters | ml_data=ml_model_parameters(ml_data, model_name, numHiddenUnits) sets |
| model_evalute | stats=model_evalute(y_true,y_pred,Conditions) evaluates predicted data |
| model_predict | model_evalute evaluates predicted data |
| model_train | Mdl=model_train(ml_data, Model_name) trains a classification model |
| sequencech | x_t=sequencech(x) converts cell array data extracted using bemech_zoo2table to a |
| stackch | x_t=stackch(x) converts cell array data extracted using bemech_zoo2table to a |
| table2ml_structure | |
| train_test_scale | ml_data = train_test_scale(ml_data, Normalize) scales ml_data using normalization schemes |
| train_test_split | TRAIN_TEST_SPLIT spliting ml_data into train test sets |
Master index