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This article presents a hybrid approach for breast tissue classification problem, where a limited dataset is available and misclassification may have severe adverse implications. Besides using classical methods in a two-stage classification setup, the method employs detailed data analysis, selection, and manipulation before each stage of classification to yield nearly zero false negative classification...
The popularity of the Internet has caused a massive increase in the amount of Web pages. The information explosion has led to a growing challenge for information retrieval systems. Document clustering becomes an important process for helping the information retrieval systems organize this vast amount of data. It is believed that grouping similar documents together into clusters will help the users...
Support vector machines (SVMs) have been applied in speaker verification successfully. But they cannot easily deal with the dynamic time structure of audio data, since they are constrained to work with fixed-length vectors. In this paper, we propose a new feature extraction approach based on PCA and improved Fisher score for the sake of solving this problem existed in SVM. This new feature extraction...
Classification can often benefit from efficient feature selection. However, the presence of linearly nonseparable data, quick response requirement, small sample problem and noisy features makes the feature selection quite challenging. In this work, a class separability criterion is developed in a high-dimensional kernel space, and feature selection is performed by the maximization of this criterion...
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