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The curse of dimensionality in machine learning we are introducing in this paper is caused by increasing data, and the research focus of feature selection is described. The formalized definitions of redundancy and relevance of feature are presented. Based on entropy and mutual information of information theory, the issue of how to measure the relevance between features is discussed. The main contributions...
In this paper, a novel method (NM) is designed for hepatitis disease diagnosis, which is based on Rough Set(RS), Particle Swarm Optimization(PSO) and Support Vector Machines(SVM). The hepatitis disease dataset is obtained from UCI machine learning dataset. The performance of the proposed method is tested on the above dataset and the result of it is compared with the results of genetic algorithm (GA)...
Due to the general lack of experimental data for biochemical pathway model identification, cell-level time series experimental design is particularly important in current systems biology research. This paper investigates the problem of experimental design for signal transduction pathway modeling, and in particular, focuses on methods for parametric feature selection. An important problem is the estimation...
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