Multiple regression output nodes in tensorflow learn
<p>I am relatively new to tensorflow and want to use the DNNRegressor from tf.contrib.learn for a regression task. But instead of one output node, I would like to have several (let's say ten for example). </p>

<p>How can I configure my regressor to adjust many output nodes to fit my needs? </p>

<p>My question is related to the following ones already asked on SO, but there seems to be no working answer (I am using TensorFlow version 0.11)</p>

<p><a href="http://stackoverflow.com/questions/34224826/skflow-regression-predict-multiple-values?rq=1">skflow regression predict multiple values</a></p>

<p><a href="http://stackoverflow.com/questions/39192107/multiple-target-columns-with-skflow-tensorflowdnnregressor">Multiple target columns with SkFlow TensorFlowDNNRegressor</a></p>

<p>It seems using tflearn will be the other choice.</p>

<p>Update: I realize we should use Keras as an well developed API for tensorflow+ theano .</p>

python tensorflow skflow