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Most of graph-based methods for semi-supervised learning are transductive, giving predictions for only the unlabeled data in the training set, and not for an arbitrary test point. SLC (Semi-supervised Local Linear Coordinate), which is based on LLC (Local Linear Coordinate) is present here as an inductive method. The mixture of factor analyzers is used to model the raw data set, and the label smoothness...
Although decision tree learning has achieved great success in building classifier, most existing methods don't pay attention to unequal weights between different instances from training and testing data sets. However, many real world data sets are imbalanced in nature. In this paper, we introduce a new improved decision tree based weights, which considers imbalanced weights between different instances,...
Ontology is more and more popular in all kinds of knowledge management system, but the manual acquisition of ontologies still remains a tedious, cumbersome task. Meanwhile moving toward semi-automation or automation of ontology construction is a solution. In this paper, we proposed a semiautomatic ontology building approach. In this approach the system starts form a small core ontology constructed...
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