python - Inserting data into regression network in keras -

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i struggling understand how should train regression network using keras. not sure how should pass input data network.

both input data , output data stored list of numpy arrays.

each input numpy array matrix has (400 rows, x columns) each output numpy array matrix has (x number of rows, 13 columns)

so input dimension 400 , output 13. how pass each of these sets within list training?

# multilayer perceptron model = sequential()    # feedforward model.add(dense(3, input_dim=400)) model.add(activation('tanh')) model.add(dense(1)) model.compile('sgd', 'mse')

just parsing data gives me error message :

traceback (most recent call last):   file "tensorflow_datapreprocess_mfcc_extraction_rnn.py", line 167, in <module>     model.fit(train_set_data,train_set_output,verbose=1)   file "/usr/local/lib/python2.7/dist-packages/keras/models.py", line 620, in fit     sample_weight=sample_weight)   file "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py", line 1034, in fit     batch_size=batch_size)   file "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py", line 961, in _standardize_user_data     exception_prefix='model input')   file "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py", line 51, in standardize_input_data     '...') exception: error when checking model input: list of numpy arrays passing model not size model expected. expected see 1 arrays instead got following list of 270 arrays: [array([[ -1.52587891e-04,   3.05175781e-05,  -1.52587891e-04,          -5.18798828e-04,   3.05175781e-05,  -3.96728516e-04,           1.52587891e-04,   3.35693359e-04,  -9.15527344e-05,           3.3...


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