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Linear laplacian discrimination for feature extraction

机译:线性拉普拉斯鉴别特征提取

摘要

An exemplary method for extracting discriminant feature of samples includes providing data for samples in a multidimensional space; based on the data, computing local similarities for the samples; mapping the local similarities to weights; based on the mapping, formulating an inter-class scatter matrix and an intra-class scatter matrix; and based on the matrices, maximizing the ratio of inter-class scatter to intra-class scatter for the samples to provide discriminate features of the samples. Such a method may be used for classifying samples, recognizing patterns, or other tasks. Various other methods, devices, system, etc., are also disclosed.
机译:用于提取样本的判别特征的示例性方法包括在多维空间中提供样本的数据。根据数据,计算样本的局部相似度;将局部相似性映射到权重;基于所述映射,形成类间散布矩阵和类内散布矩阵;并基于矩阵,最大化样本的类间散布与类内散布的比率​​,以提供样本的区分特征。这样的方法可用于分类样本,识别模式或其他任务。还公开了各种其他方法,设备,系统等。

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