fault_train
Prototype
def fault_train(data_path, model_path, param)
Description
Fault training interface. It is used to train a new model.
Working Principle
Reads data and parameters to train a new model and dump the model file for prediction. In addition, this interface outputs the verification results of machine learning training metrics to a log file, including precision, recall (also called fault detection rate in the fault prediction field), FPR (also called false alarm rate in the fault prediction field), F1 score, and accuracy.
Fault detection rate in the fault prediction field corresponds to recall in the machine learning field. False alarm rate in the fault prediction field corresponds to false positive rate in the machine learning field.
Parameters
Parameter |
Description |
Input/Output |
|---|---|---|
data_path |
Path to the data file to be trained |
Input |
model_path |
Model file dump path |
Input |
param |
Training parameters |
Input |