I'm trying to implement the One Hidden Layer Model presented in this article using Keras.
This is my code:
from keras.models import Sequential from keras.layers import Dense, Dropout, Flatten, Activation from keras import optimizers model = Sequential() model.add(Dense(100, input_dim=9216)) model.add(Activation('relu')) model.add(Dense(30)) model.compile(loss='mean_squared_error', optimizer=sgd, metrics=['accuracy']) sgd = optimizers.SGD(lr=0.01, momentum=0.9, nesterov=True) hist = model.fit(X_train, y_train, epochs=10, verbose=0, validation_split=0.2) y_pred = model.predict_classes(X_valid)
X_train shape is (2140, 9216)
y_train shape is (2140, 30)
X_valid shape is (1783, 9216)
y_valid shape is (1783,). I'm trying to understand why I'm not getting a (1783, 30) output. Am I missing something?