Package org.shapelogic.machinelearning

Class Summary

ConfidenceArraySelector	ConfidenceArraySelector takes a double[] and creates a String. Translates a double[] that could come from a neural network to either the number of the one that is winning walue if any is or to a name for that.
ExampleNeuralNetwork	ExampleNeuralNetwork for use in default neural network.
FFNeuralNetwork	Feed Forward Neural Network with external training.
FFNeuralNetworkStream	FFNeuralNetworkStream a feed forward neural network wrapped in a stream. Streams involved: ArrayOutputListStream: A list of names of input features that need to be streams FFNeuralNetwork: Creates stream of double[] from the neural network ConfidenceArrayListStream: Creat result stream of String Which of these needs names? None of them. It seems like the last stream will have the same output as the overall stream is the overall then really needed? No. There should probably be a stack of Streams. This could possibly be a LISP list, no there is no advantage to this. The whole think should be created lazily, but when it gets created, you can directly pipe one into the next. What should trigger the setup? As long as the first have a lazy setup we should be fine and it does. So the first should be any type of ListStream, while the next have to be ListCalcStream1 or any ListStream with one input.
FFNeuralNetworkWeights	FFNeuralNetworkWeights represent a trained feed forward neural network.
FFNeuralNetworkWeightsParser	FFNeuralNetworkWeightsParser parses FFNeuralNetworkWeights. syntax: BLOCK_START "FEATURES" string + BLOCK_START "RESULTS" string + BLOCK_START ("WEIGHTS" number + BLOCK_START ) * "WEIGHTS" number