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# GeneralizedLinearRegressionSummary 

#### class GeneralizedLinearRegressionSummary extends Serializable

Summary of GeneralizedLinearRegression model and predictions.

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@Since( "2.0.0" )
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GeneralizedLinearRegression.scala
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### Value Members

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4. lazy val aic: Double

Akaike Information Criterion (AIC) for the fitted model.

Akaike Information Criterion (AIC) for the fitted model.

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@Since( "2.0.0" )
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6. def clone()
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7. lazy val degreesOfFreedom: Long

Degrees of freedom.

Degrees of freedom.

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@Since( "2.0.0" )
8. lazy val deviance: Double

The deviance for the fitted model.

The deviance for the fitted model.

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@Since( "2.0.0" )
9. lazy val dispersion: Double

The dispersion of the fitted model.

The dispersion of the fitted model. It is taken as 1.0 for the "binomial" and "poisson" families, and otherwise estimated by the residual Pearson's Chi-Squared statistic (which is defined as sum of the squares of the Pearson residuals) divided by the residual degrees of freedom.

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@Since( "2.0.0" )
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16. val

Private copy of model to ensure Params are not modified outside this class.

Private copy of model to ensure Params are not modified outside this class. Coefficients is not a deep copy, but that is acceptable.

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protected
Note

predictionCol must be set correctly before the value of model is set, and model must be set before predictions is set!

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20. lazy val nullDeviance: Double

The deviance for the null model.

The deviance for the null model.

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@Since( "2.0.0" )
21. lazy val numInstances: Long

Number of instances in DataFrame predictions.

Number of instances in DataFrame predictions.

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@Since( "2.2.0" )
22. val predictionCol: String

Field in "predictions" which gives the predicted value of each instance.

Field in "predictions" which gives the predicted value of each instance. This is set to a new column name if the original model's `predictionCol` is not set.

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@Since( "2.0.0" )
23. val predictions

Predictions output by the model's `transform` method.

Predictions output by the model's `transform` method.

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@Since( "2.0.0" )
24. lazy val rank: Long

The numeric rank of the fitted linear model.

The numeric rank of the fitted linear model.

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@Since( "2.0.0" )
25. lazy val residualDegreeOfFreedom: Long

The residual degrees of freedom.

The residual degrees of freedom.

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@Since( "2.0.0" )
26. lazy val residualDegreeOfFreedomNull: Long

The residual degrees of freedom for the null model.

The residual degrees of freedom for the null model.

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@Since( "2.0.0" )
27. def residuals(residualsType: String)

Get the residuals of the fitted model by type.

Get the residuals of the fitted model by type.

residualsType

The type of residuals which should be returned. Supported options: deviance, pearson, working and response.

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@Since( "2.0.0" )
28. def residuals()

Get the default residuals (deviance residuals) of the fitted model.

Get the default residuals (deviance residuals) of the fitted model.

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@Since( "2.0.0" )
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