def prepare_model(ninputs=9600, nclass=5):
 lrmodel = Sequential()
 lrmodel.add(Dense(ninputs, nclass))
 lrmodel.add(Activation('softmax'))
 lrmodel.compile(loss='categorical_crossentropy', optimizer='adam')
 return lrmodel

def prepare_model ( ninputs = 9600 , nclass = 5 ) : lrmodel = Sequential ( ) lrmodel . add ( Dense ( ninputs , nclass ) ) lrmodel . add ( Activation ( 'softmax' ) ) lrmodel . compile ( loss = 'categorical_crossentropy' , optimizer = 'adam' ) return lrmodel
set up and compile the model architecture .