Class DataframeAnalysisClassification.Builder
java.lang.Object
co.elastic.clients.elasticsearch.ml.DataframeAnalysisBase.AbstractBuilder<DataframeAnalysisClassification.Builder>
co.elastic.clients.elasticsearch.ml.DataframeAnalysisClassification.Builder
- All Implemented Interfaces:
ObjectBuilder<DataframeAnalysisClassification>
- Enclosing class:
- DataframeAnalysisClassification
public static class DataframeAnalysisClassification.Builder extends DataframeAnalysisBase.AbstractBuilder<DataframeAnalysisClassification.Builder> implements ObjectBuilder<DataframeAnalysisClassification>
Builder for
DataframeAnalysisClassification
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Constructor Summary
Constructors Constructor Description Builder()
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Method Summary
Modifier and Type Method Description DataframeAnalysisClassification
build()
Builds aDataframeAnalysisClassification
.DataframeAnalysisClassification.Builder
classAssignmentObjective(java.lang.String value)
API name:class_assignment_objective
DataframeAnalysisClassification.Builder
numTopClasses(java.lang.Integer value)
Defines the number of categories for which the predicted probabilities are reported.protected DataframeAnalysisClassification.Builder
self()
Methods inherited from class co.elastic.clients.elasticsearch.ml.DataframeAnalysisBase.AbstractBuilder
addFeatureProcessors, addFeatureProcessors, alpha, dependentVariable, downsampleFactor, earlyStoppingEnabled, eta, etaGrowthRatePerTree, featureBagFraction, featureProcessors, featureProcessors, featureProcessors, gamma, lambda, maxOptimizationRoundsPerHyperparameter, maxTrees, numTopFeatureImportanceValues, predictionFieldName, randomizeSeed, softTreeDepthLimit, softTreeDepthTolerance, trainingPercent
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Constructor Details
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Builder
public Builder()
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Method Details
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classAssignmentObjective
public DataframeAnalysisClassification.Builder classAssignmentObjective(@Nullable java.lang.String value)API name:class_assignment_objective
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numTopClasses
Defines the number of categories for which the predicted probabilities are reported. It must be non-negative or -1. If it is -1 or greater than the total number of categories, probabilities are reported for all categories; if you have a large number of categories, there could be a significant effect on the size of your destination index. NOTE: To use the AUC ROC evaluation method,num_top_classes
must be set to -1 or a value greater than or equal to the total number of categories.API name:
num_top_classes
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self
- Specified by:
self
in classDataframeAnalysisBase.AbstractBuilder<DataframeAnalysisClassification.Builder>
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build
Builds aDataframeAnalysisClassification
.- Specified by:
build
in interfaceObjectBuilder<DataframeAnalysisClassification>
- Throws:
java.lang.NullPointerException
- if some of the required fields are null.
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