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These are all of the apply functions parameters that can be specified:
Cluster ID: The default is Most Probable. No other parameters are supported.
Cluster Probability: The default is Most Probable. You can also select a specific cluster ID or specify NULL or Most Likely to return the bounds for the most likely cluster.
Cluster Set: The default: is All Clusters. You can also specify either or both of the following:
TopN where N is between 1 and the number of clusters. The optional topN argument is a positive integer that restricts the set of features to those that have one of the top N values. If there is a tie at the Nth value, then the database still returns only N values. If you omit this argument, then the function returns all features.
Probability Cutoff is a number strictly greater than 0 and less than or equal to 1. The optional cutoff argument restricts the returned features to only those that have a feature value greater than or equal to the specified cutoff. To filter only by cutoff, specify NULL for topN and the desired cutoff for cutoff.
Feature ID: The default is Most Probable. No other values are supported.
Feature Set: The default is All Feature IDs. You can also specify either or both of the following:
TopN where N is between 1 and the number of clusters. The optional topN argument is a positive integer that restricts the set of features to those that have one of the top N values. If there is a tie at the Nth value, then the database still returns only N values. If you omit this argument, then the function returns all features.
Probability Cutoff is a number strictly greater than 0 and less than or equal to 1. The optional cutoff argument restricts the returned features to only those that have a feature value greater than or equal to the specified cutoff. To filter only by cutoff, specify NULL for topN and the desired cutoff for cutoff.
Feature Value: The default is Highest Value. You can also select a specific feature ID value or specify NULL or Most Likely to return the bounds for the most likely feature.
Prediction: The default is Best Prediction to take account of a cost matrix.
Prediction Upper Bounds or Prediction Lower Bounds: The default is Best Prediction with Confidence Level 95%. You can change Confidence Level to any number strictly greater than 0 and less than or equal to 1. For Classification models only, you can use the Target Value Selection box option to pick a specific target value. You can also specify NULL or Most Likely to return the bounds for the most likely target value.Prediction Costs: The default is Best Prediction. For Classification models only, you can use the Target Value Selection box option to pick a specific target value.
Prediction Details: Only value is the details for the Best Prediction.
Prediction Probability: The default is Best Prediction. For Classification models only, you can use the Target Value Selection box option to pick a specific target value.
Prediction Set: The default is All Target Values. You can also specify one or both of the following:
bestN where N is between 1 and the number of targets. The optional bestN argument is a positive integer that restricts the returned target classes to the N having the highest probability, or lowest cost if cost matrix clause is specified. If multiple classes are tied in the Nth value, then the database still returns only N values. If you want to filter only by cutoff, specify NULL for this parameter.
Probability Cutoff is a number strictly greater than 0 and less than or equal to 1. The optional cutoff argument restricts the returned target classes to those with a probability greater than or equal to (or a cost less than or equal to if cost matrix clause is specified) the specified cutoff value. You can filter solely by cutoff by specifying NULL for this value.