Help needed to build a binary classifier using neural network to classify electrical faults

Hello,

I am trying to build a binary classifier to detect High Impedance Faults from simulated data using neural net designer app. I am stuck with how to input the data table in the classifier network. My data consists of Voltage and Current values of all three phases and a Fault Status variable.

These are the steps I am taking:

1. In the Deep Network Designer app, I added the desired layers and exported the model into workspace.
2. In the transfer learning app, when I trying to select the .mat file created in the step 1, it shows me an error as below:

Basically, I am stuck with how to import data (Datastore) into the transfer learning app.

Thanks.

Answer 1

[Bhargavi Maganuru]

Hi,

To import model from mat file, select import mat file model in drop down menu of Pre-Trained model and then press continue in the pop up that comes up. Now it will ask for .mat file, select the corresponding .mat file.

If images stored in folder according to their category, then import only the main folder - using import data(Datastore)

Follow this link for the example.

Hope this helps!