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In this paper we propose a Sequential Ensemble Classification (SEC) technique which is designed to tackle the problem of learning from a data set with an extremely unbalanced distribution of instances among the classes. This system employs a specific decomposition technique that reduces the degree of unbalance in the data by transforming multi-class problem into a sequence of binary class problems...
In this paper we present a Dynamic Sampling Framework for use with multi-class imbalanced data containing any number of classes. The framework makes use of existing sampling techniques such as RUS, ROS, and SMOTE and ties the classification algorithm into the sampling process in a wrapper like manner. In doing so the framework is able to search for a desirably sampled training set, thus eliminating...
This paper presents an intelligent steganalysis method to investigate anomalies in Waveform Audio File Format (Wave). There are many images and audio file formats available to hide sensitive information without attracting attentions. Steganalysis is a set of techniques to reveal secrets in audio, video or other file formats. Image based stego analysis is fairly simple because hiding methods such as...
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