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EBK Regression Prediction - overlap factor

Question asked by ahooperesriaustralia-com-au-esridist Employee on Oct 26, 2017
Latest reply on Oct 26, 2017 by ahooperesriaustralia-com-au-esridist

Are there any resources available which provide further detail on overlap factor?

 

A factor representing the degree of overlap between local models (also called subsets). Each input point can fall into several subsets, and the overlap factor specifies the average number of subsets that each point will fall into. A high value of the overlap factor makes the output surface smoother, but it also increases processing time. Values must be between 1 and 5. If Subset polygon features are supplied, the value of this parameter will be ignored.

 

My assumption is that if the value is 1, all input points can only exist in one local model.

If the value is 2, all input points can exist in one or two local models.

Any information on the models justification for allowing an input point to be used in 1 or 2 or more local models would be appreciated.

 

Cheers.

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