predict probabilities using LSTM

Hi all

I am trying to create a predict probabilities model using LSTM for predicting 5 different classes. I am just wondering is it possible to have the output of the prediction model using LSTM as a vector of belonging values to each class, not as a crisp value? In other words, if I have to predict 5 different classes, when I use the prediction process, I want to have the results as a vector of belonging degrees to each output class for each instance such as:

pred_out= [0.025, 0.8, 0.00058, 0.225. 0.07]. So, the highest value for class number 2. Any ideas, please.

Thanks in advance

Gad

Answer 1

[Ankit Kumar]

Hi Gadelhag,

You can use

[YPred, scores] = classify(net,sequences)

Here scores give you the probabilities of different classes that you want.

For more about classify function refer,

https://in.mathworks.com/help/deeplearning/ref/classify.html#d117e99562