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BANDWIDTH SELECTION IN SUPPORT VECTOR DATA DESCRIPTION FOR CLASSIFICATION OR OUTLIER DETECTION
BANDWIDTH SELECTION IN SUPPORT VECTOR DATA DESCRIPTION FOR CLASSIFICATION OR OUTLIER DETECTION
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机译:支持向量数据描述中的带宽选择,用于分类或异常检测
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摘要
A computing device determines a bandwidth parameter value for outlier detection or data classification. A mean pairwise distance value is computed between observation vectors. A tolerance value is computed based on a number of observation vectors. A scaling factor value is computed based on a number of observation vectors and the tolerance value. A Gaussian bandwidth parameter value is computed using the mean pairwise distance value and the scaling factor value. An optimal value of an objective function is computed that includes a Gaussian kernel function that uses the computed Gaussian bandwidth parameter value. The objective function defines a support vector data description model using the observation vectors to define a set of support vectors. The Gaussian bandwidth parameter value and the set of support vectors are output for determining if a new observation vector is an outlier or for classifying the new observation vector.
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