skflow regression predict multiple values

Question

I\'m trying to forecast a time series: given 50 previous values, I want to predict the 5 next values.

To do so, I\'m using the skflow package (based on

Answer 1

I've just added support for multi-output regression into skflow since this #e443c734, so please reinstall the package are try again. If it doesn't work, please follow up on Github.

I also added an example of multioutput regression to examples folder:

# Create random dataset.
rng = np.random.RandomState(1)
X = np.sort(200 * rng.rand(100, 1) - 100, axis=0)
y = np.array([np.pi * np.sin(X).ravel(), np.pi * np.cos(X).ravel()]).T

# Fit regression DNN model.
regressor = skflow.TensorFlowDNNRegressor(hidden_units=[5, 5])
regressor.fit(X, y)
score = mean_squared_error(regressor.predict(X), y)
print("Mean Squared Error: {0:f}".format(score))