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The linear discriminant analysis (LDA) is one of the most efficient supervised dimensionality reduction technique widely used in face recognition. This paper proposed a new weighted LDA to improve the performance of the discriminant analysis. Confusable pair of classes is considered as the primary goal in our objective function. The proposed technique not only improves the minimization of the within-class...
Coughing is one of the important signs of several diseases in dogs. There are two types of dog cough: dry cough and productive cough. The latter is most often associated with an infectious condition. It is difficult to differentiate between the two types even by experienced practitioners. In this paper, an automatic cough sound classification using neural network is introduced. A discrete wavelet...
An understanding of success factor relationships in the context of business-to-business where Inter-organizational Relationship (IORs) between organizations is crucial for effective strategic management to accomplish marketing goals. Several studies regarding those success factors and their influences have been conducted and published as articles. We apply the technique of Named Entity Recognition...
Thyroid cancer is a common endocrine tumor that is experiencing a steady increase in incidence worldwide. The latest discoveries on disease and its treatment are mostly propagated in the form of biomedical publications such as those in PubMed. Unfortunately, this information is distributed in unstructured text with over two thousand articles being added annually. Text mining technology plays an important...
In the context of Business-to-Business (B2B), an understanding of inter-organizational success factors and their impacts is crucial for effective strategic management. Several studies regarding those success factors and their influences have been conducted and published as articles. We aim at applying existing techniques, especially data mining, to automatically classify relevant sentences describing...
This paper proposes an unsupervised discrimination analysis for feature selection based on a property of the Fourier transform of the probability density distribution. Each feature is evaluated on the basis of a simple observation motivated by the concept of optical diffraction, which is invariant under feature scaling. The time complexity is , where is number of features and is number of...
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