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Determining a preferred node in a classification and regression tree for use in a predictive analysis
Determining a preferred node in a classification and regression tree for use in a predictive analysis
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机译:确定分类和回归树中的首选节点以用于预测分析
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摘要
Techniques are described for determining what node of a classification and regression tree (CART) should be used by a predictive analysis application. A first approach is to use a standard deviation of the data at a given the level of the CART to determine whether data in the next, lower node is more consistent than the data in the current node. A second approach is to measure a correlation between data points in a given node and the time at which each point was sampled (or other correlation metric) to identify a preferred node.
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