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Mining Health Examination Records – A Graph-based Approach Abstract?General health examination is an integral part of healthcare in many countries. Identifying the participants at risk is important for early warning and preventive intervention. The fundamental challenge of learning a classification model for risk prediction lies in the unlabeled data that constitutes the majority of the…
On Learning of Choice Models with Interactive Attributes Abstract?Introducing recent advances in the machine learning techniques to state-of-the-art discrete choice models, we develop an approach to infer the unique and complex decision making process of a decision-maker (DM), which is characterized by the DM?s priorities and attitudinal character, along with the attributes interaction, to name…
Toward Optimal Feature Selection in Naive Bayes for Text Categorization Abstract?Automated feature selection is important for text categorization to reduce the feature size and to speed up the learning process of classifiers. In this paper, we present a novel and efficient feature selection framework based on the Information Theory, which aims to rank the features…
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