Machine trained network using novel coding techniques

Abstract

Some embodiments of the invention provide a machine-trained method that selects an output from a plurality of outputs by processing an input. The method uses layers of machine-trained processing nodes to process the input to produce a multi-dimensional codeword. The method generates a set of affinity scores with each affinity score identifying the proximity of the produced codeword to a codeword in a first set of previously defined codewords. The method compares the set of affinity scores generated for the produced codeword with sets of affinity scores previously generated for the first-set codewords that express the proximity of the first-set codewords to a second set of codewords. The method identifies the first-set codeword that has the affinity score set that best matches the affinity score set generated for the produced codeword. The method selects the associated output of the identified first-set codeword as the output of the network.