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In this paper, we propose a novel method for incremental semi-supervised learning. Unlike the traditional way of incremental learning or semi-supervised learning, we try to answer a more challenging question: given inadequate labeled training data, can one use the unlabeled testing data to improve the learning and prediction accuracy? The objective here is to reinforce the learning system trained...
Feature selection is an active research area in machine learning for high dimensional dataset analysis. The idea is to perform the learning process solely on the top ranked feature spaces instead of the entire original feature space, and therefore to improve the understanding of the inherent characteristics of such dataset as well as reduce the computational cost. While most of the research efforts...
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