Large scale manifold transduction that predicts class labels with a neural network and uses a mean of the class labels

An apparatus for use in discriminative classification and regression, the apparatus comprising:

• an input device for inputting unlabeled datapoints associated with a phenomenon of interest;
• a processor;
• and
• a memory communicating with the processor, the memory comprising instructions executable by the processor for training a neural network by:
• randomly selecting one of the unlabeled datapoints associated with the phenomenon of interest;
• determining a set of datapoints associated with the phenomenon of interest that are likely to be in the same class as the selected unlabeled datapoint;
• predicting with the neural network a class label for the selected unlabeled datapoint;
• predicting with the neural network a class label for the set of datapoints, the class label comprising a number;
• combining the predicted class labels by taking a mean of the class labels to predict a composite class label that describes the selected unlabeled datapoint and the set of datapoints;
• and
• using the combined class label to adjust at least one parameter of the neural network.