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ENVISVMClassifier::Classify

ENVISVMClassifier::Classify

The Classify method returns an array of class values corresponding to the data provided. This method is meant for use with non-image data sources. It is typically called after the classifier has been trained by a trainer. The data are contained in an ENVIExamples object and must contain the same attributes, in the same order, and with the same representation (for example, normalized) as the examples used to train the classifier. This method determines a class value for each data example. It always assigns a value and does not create unclassified data examples.

Syntax


Result = ENVISVMClassifier.Classify(Examples [, Keywords=value])

Return Value


This method returns an array of class values corresponding to the data provided.

Arguments


Examples

Specify an ENVIExamples object.

Keywords


ACTIVATION (optional)

Set this keyword to the name of an activation value array of size m classes by n examples. For each example, the Support Vector Machine (SVM) activation function calculates the probability that it belongs to each class. The chosen class is the one with the highest probability for that example. If classification does not perform as expected, the activation values can be analyzed to compare the probabilities of the expected and chosen classes.

ERROR (optional)

Set this keyword to a named variable that will contain any error message issued during execution of this routine. If no error occurs, the ERROR variable will be set to a null string (''). If an error occurs and the routine is a function, then the function result will be undefined.

When this keyword is not set and an error occurs, ENVI returns to the caller and execution halts. In this case, the error message is contained within !ERROR_STATE and can be caught using IDL's CATCH routine. See IDL Help for more information on !ERROR_STATE and CATCH.

See Manage Errors for more information on error handling in ENVI programming.

Version History


ENVI 5.4

Introduced

API Version


3.2

See Also


ENVISVMClassifier



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