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Statistical classification methods applied to seismic discrimination

机译：应用于地震判别的统计分类方法

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摘要

This report provides background information on various statistical classification methods and discusses the relevance of each method in the Comprehensive Test Ban Treaty (CTBT) seismic discrimination setting. Criteria for classification method selection are explained and examples are given to illustrate several key issues. Section 2 of this report describes both the CTBT seismic discrimination setting and the general statistical classification approach to this setting. Classification method selection criteria are presented and discussed in Section 3. These criteria are grouped into the broad classes of simplicity, robustness, applicability, and performance. Section 4 follows with a description of several statistical classification methods: linear discriminant analysis, quadratic discriminant analysis, variably regularized discriminant analysis, flexible discriminant analysis, logistic discriminant analysis, K-th Nearest Neighbor discrimination, kernel discrimination, and classification and regression tree discrimination. The advantages and disadvantages of these methods are summarized in Section 5.

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