MLP Classifier in Python

Asked Dec 28 '20 at 07:34

Active Dec 28 '20 at 07:34

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I am new to machine learning and I have been trying to implement a neural network in Python using Keras library. I want to implement a MLP classifier for a multi-classification problem with input dimension of [34310,33] with the output dimension as [34310,66] formed using one hot label. enter image description here

I have included the architecture of the MLP classifier above in the link. I have tried to create the same in the python and I have pasted the lines below.

model = Sequential()
model.add(Dense(100, input_dim = 33, activation = 'relu'))
model.add(Dense(66, activation = 'softmax'))
model.compile(loss='categorical_crossentropy', optimizer='adam',metrics = ['accuracy'])

Could you please provide some validation for the above lines of code?

asked Dec 28 '20 at 07:34

RS A

Can you explain what you mean by saying your 66 output neurons were formed using one hot label? – Gaussian Prior Dec 28 '20 at 12:22
Actually, there are a total of 66 classes which I represented in one hot label form for each sample – RS A Dec 28 '20 at 16:30

MLP Classifier in Python

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