Class DataframeEvaluationRegressionMetrics.Builder
java.lang.Object
co.elastic.clients.util.ObjectBuilderBase
co.elastic.clients.elasticsearch.ml.DataframeEvaluationRegressionMetrics.Builder
- All Implemented Interfaces:
ObjectBuilder<DataframeEvaluationRegressionMetrics>
- Enclosing class:
- DataframeEvaluationRegressionMetrics
public static class DataframeEvaluationRegressionMetrics.Builder extends ObjectBuilderBase implements ObjectBuilder<DataframeEvaluationRegressionMetrics>
Builder for
DataframeEvaluationRegressionMetrics
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Constructor Summary
Constructors Constructor Description Builder()
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Method Summary
Modifier and Type Method Description DataframeEvaluationRegressionMetrics
build()
Builds aDataframeEvaluationRegressionMetrics
.DataframeEvaluationRegressionMetrics.Builder
huber(DataframeEvaluationRegressionMetricsHuber value)
Pseudo Huber loss function.DataframeEvaluationRegressionMetrics.Builder
huber(java.util.function.Function<DataframeEvaluationRegressionMetricsHuber.Builder,ObjectBuilder<DataframeEvaluationRegressionMetricsHuber>> fn)
Pseudo Huber loss function.DataframeEvaluationRegressionMetrics.Builder
mse(java.lang.String key, JsonData value)
Average squared difference between the predicted values and the actual (ground truth) value.DataframeEvaluationRegressionMetrics.Builder
mse(java.util.Map<java.lang.String,JsonData> map)
Average squared difference between the predicted values and the actual (ground truth) value.DataframeEvaluationRegressionMetrics.Builder
msle(DataframeEvaluationRegressionMetricsMsle value)
Average squared difference between the logarithm of the predicted values and the logarithm of the actual (ground truth) value.DataframeEvaluationRegressionMetrics.Builder
msle(java.util.function.Function<DataframeEvaluationRegressionMetricsMsle.Builder,ObjectBuilder<DataframeEvaluationRegressionMetricsMsle>> fn)
Average squared difference between the logarithm of the predicted values and the logarithm of the actual (ground truth) value.DataframeEvaluationRegressionMetrics.Builder
rSquared(java.lang.String key, JsonData value)
Proportion of the variance in the dependent variable that is predictable from the independent variables.DataframeEvaluationRegressionMetrics.Builder
rSquared(java.util.Map<java.lang.String,JsonData> map)
Proportion of the variance in the dependent variable that is predictable from the independent variables.Methods inherited from class co.elastic.clients.util.ObjectBuilderBase
_checkSingleUse, _listAdd, _listAddAll, _mapPut, _mapPutAll
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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mse
public final DataframeEvaluationRegressionMetrics.Builder mse(java.util.Map<java.lang.String,JsonData> map)Average squared difference between the predicted values and the actual (ground truth) value. For more information, read this wiki article.API name:
mse
Adds all entries of
map
tomse
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mse
public final DataframeEvaluationRegressionMetrics.Builder mse(java.lang.String key, JsonData value)Average squared difference between the predicted values and the actual (ground truth) value. For more information, read this wiki article.API name:
mse
Adds an entry to
mse
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msle
public final DataframeEvaluationRegressionMetrics.Builder msle(@Nullable DataframeEvaluationRegressionMetricsMsle value)Average squared difference between the logarithm of the predicted values and the logarithm of the actual (ground truth) value.API name:
msle
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msle
public final DataframeEvaluationRegressionMetrics.Builder msle(java.util.function.Function<DataframeEvaluationRegressionMetricsMsle.Builder,ObjectBuilder<DataframeEvaluationRegressionMetricsMsle>> fn)Average squared difference between the logarithm of the predicted values and the logarithm of the actual (ground truth) value.API name:
msle
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huber
public final DataframeEvaluationRegressionMetrics.Builder huber(@Nullable DataframeEvaluationRegressionMetricsHuber value)Pseudo Huber loss function.API name:
huber
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huber
public final DataframeEvaluationRegressionMetrics.Builder huber(java.util.function.Function<DataframeEvaluationRegressionMetricsHuber.Builder,ObjectBuilder<DataframeEvaluationRegressionMetricsHuber>> fn)Pseudo Huber loss function.API name:
huber
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rSquared
public final DataframeEvaluationRegressionMetrics.Builder rSquared(java.util.Map<java.lang.String,JsonData> map)Proportion of the variance in the dependent variable that is predictable from the independent variables.API name:
r_squared
Adds all entries of
map
torSquared
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rSquared
public final DataframeEvaluationRegressionMetrics.Builder rSquared(java.lang.String key, JsonData value)Proportion of the variance in the dependent variable that is predictable from the independent variables.API name:
r_squared
Adds an entry to
rSquared
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build
Builds aDataframeEvaluationRegressionMetrics
.- Specified by:
build
in interfaceObjectBuilder<DataframeEvaluationRegressionMetrics>
- Throws:
java.lang.NullPointerException
- if some of the required fields are null.
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