Efficient training of models with large number of input features (>10k)

tensorflow / decision-forests

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

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Efficient training of models with large number of input features (>10k) #36

Open achoum opened 3 years ago

achoum commented 3 years ago

Background

Currently, the training graph contains one tf op for each input features. In case of large number of features (or in the case of multi dimensional features), this can lead to a large overhead (large memory consumption, large training initialization stage).

Features request

Support for multi dimensional features without creating an op for each dimension.