METHOD FOR DETERMINING A PREFERRED NODE IN A CLASSIFICATION AND REGRESSION TREE FOR USE IN A PREDICTIVE ANALYSIS

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 mor...

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Bibliographic Details
Main Authors ARNDT KARLA K, CAFFREY JAMES M, PAYTON ASPEN L
Format Patent
LanguageEnglish
Published 18.04.2013
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary: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.
Bibliography:Application Number: US201213705286