| Class | Description |
|---|---|
| FeedForwardWithKeyFunction<K> |
Function to feed-forward examples, and get the network output (for example, class probabilities).
|
| ScoreExamplesFunction |
Function to score examples individually.
|
| ScoreExamplesWithKeyFunction<K> |
Function to score examples individually, where each example is associated with a particular key
Note that scoring is batched for computational efficiency. This is the Spark implementation of t he MultiLayerNetwork.scoreExamples(DataSet, boolean) methodNote: The DataSet objects passed in must have exactly one example in them (otherwise: can't have a 1:1 association between keys and data sets to score) |
| ScoreFlatMapFunction | |
| VaeReconstructionErrorWithKeyFunction<K> |
Function to calculate the reconstruction error for a variational autoencoder, that is the first layer in a
MultiLayerNetwork.
Note that the VAE must be using a loss function, not a ReconstructionDistributionAlso note that scoring is batched for computational efficiency. |
| VaeReconstructionProbWithKeyFunction<K> |
Function to calculate the reconstruction probability for a variational autoencoder, that is the first layer in a
MultiLayerNetwork.
Note that scoring is batched for computational efficiency. |