Carlos-Francisco Méndez-Cruz

Deep Learning Workshop

......@@ -136,8 +136,15 @@ if __name__ == "__main__":
# Model definition
model = Sequential()
model.add(Conv1D(filters=32, kernel_size=12,
input_shape=(train_features.shape[1], 4)))
# Original considering only 4 nucleotides:
# model.add(Conv1D(filters=32, kernel_size=12,
# input_shape=(train_features.shape[1], 4)))
# We change for 5 nucleotides, as we added X:
# Do we have to change kernel_size to 15, becaause of the 5 nucleotides?
model.add(Conv1D(filters=32, kernel_size=15,
input_shape=(train_features.shape[1], 5)))
# Original: model.add(MaxPooling1D(pool_size=4))
# Do we have to change to 5, because of the 5 nucleotides?
model.add(MaxPooling1D(pool_size=4))
model.add(Flatten())
model.add(Dense(16, activation='relu'))
......