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predict probabilities using LSTM

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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

Accepted Answer

Ankit Kumar
Ankit Kumar on 21 Oct 2019
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,

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