class RuleSet extends PmmlElement
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new
RuleSet(ruleSelectionMethods: Array[RuleSelectionMethod], scoreDistributions: ScoreDistributions, rules: Array[Rule], recordCount: Option[Int], nbCorrect: Option[Int], defaultScore: Option[Any], defaultConfidence: Option[Double])
- ruleSelectionMethods
specifies how to select rules from the ruleset to score a new case. If more than one method is included, the first method is used as the default method for scoring, but the other methods included may be selected by the application wishing to perform scoring as valid alternative methods.
- scoreDistributions
describe the distribution of the predicted value in the test/training data.
- rules
contains 0 or more rules which comprise the ruleset.
- recordCount
The number of training/test cases to which the ruleset was applied to generate support and confidence measures for individual rules.
- nbCorrect
indicates the number of training/test instances for which the default score is correct.
- defaultScore
The value of score in a RuleSet serves as the default predicted value when scoring a case no rules in the ruleset fire.
- defaultConfidence
provides a confidence to be returned with the default score (when scoring a case and no rules in the ruleset fire).
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- val defaultConfidence: Option[Double]
- val defaultScore: Option[Any]
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- def fire(series: Series): Array[SimpleRule]
- def first(series: Series): Option[SimpleRule]
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- val nbCorrect: Option[Int]
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- val recordCount: Option[Int]
- val ruleSelectionMethods: Array[RuleSelectionMethod]
- val rules: Array[Rule]
- val scoreDistributions: ScoreDistributions
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