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This paper focuses on the problem of making decisions in the context of nominal data under specific constraints. The underlying goal driving the methodology proposed here is to build a decision-making model capable of classifying as many samples as possible while avoiding false positives at all costs, all within the smallest possible computational time.(More)
In this paper, a two-stage methodology to analyze and detect behavioral-based malware is presented. In the first stage, a random projection is decreasing the variable dimensionality of the problem and is simultaneously reducing the computational time of the classification task by several orders of magnitude. In the second stage, a modified K-Nearest(More)
The opinions, findings, and conclusions or recommendations expressed herein are those of the author(s) and do not necessarily reflect the views of the U.S. Agency for International Development. Abstract Mortgage markets are coming of age in a number of Eastern Europe and CIS countries. As they do, governments are looking to mortgage-loan associated subsidy(More)
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