International Business Machines Corporation
Pre-training neural networks using data clusters

Abstract:

Aspects of the present invention disclose a method, computer program product, and system for pre-training a neural network. The method extracting features of data set received from a source, the data set includes labelled data and unlabeled data. Generating a plurality of data clusters from instances of data in the data set, the data clusters are weighted according to a respective number of similar instances of labeled data and unlabeled data within a respective data cluster. Determining a data label indicating a data class that corresponds to labeled data within a data cluster of the generated plurality of data clusters. Applying the determined data label to unlabeled data within the data cluster of the generated plurality of data clusters. In response to applying the determined data label to unlabeled data within the data cluster of the generated plurality of data clusters, deploying the data cluster to a neural network.