water.bindings.pojos

Class ModelMetricsGLRMV99

java.lang.Object

water.bindings.pojos.Schema

water.bindings.pojos.ModelMetricsBase

water.bindings.pojos.ModelMetricsGLRMV99

public class ModelMetricsGLRMV99
extends ModelMetricsBase

Field Summary

Fields

Modifier and Type	Field and Description
long	catcnt Number of Non-Missing Categorical Values
double	caterr Misclassification Error (Categorical Cols)
java.lang.String	description Optional description for this scoring run (to note out-of-bag, sampled data, etc.)
java.lang.String	frame The frame used for this scoring run.
long	frame_checksum The checksum for the frame used for this scoring run.
java.lang.String	model The model used for this scoring run.
ModelCategory	model_category The category (e.g., Clustering) for the model used for this scoring run.
long	model_checksum The checksum for the model used for this scoring run.
double	MSE The Mean Squared Error of the prediction for this scoring run.
long	numcnt Number of Non-Missing Numeric Values
double	numerr Sum of Squared Error (Numeric Cols)
FrameV3	predictions Predictions Frame.
long	scoring_time The time in mS since the epoch for the start of this scoring run.

Constructor Summary

Constructors

Constructor and Description
ModelMetricsGLRMV99()

Method Summary

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

numerr

public double numerr

Sum of Squared Error (Numeric Cols)

caterr

public double caterr

Misclassification Error (Categorical Cols)

numcnt

public long numcnt

Number of Non-Missing Numeric Values

catcnt

public long catcnt

Number of Non-Missing Categorical Values

model

public java.lang.String model

The model used for this scoring run.

model_checksum

public long model_checksum

The checksum for the model used for this scoring run.

frame

public java.lang.String frame

The frame used for this scoring run.

frame_checksum

public long frame_checksum

The checksum for the frame used for this scoring run.

description

public java.lang.String description

Optional description for this scoring run (to note out-of-bag, sampled data, etc.)

model_category

public ModelCategory model_category

The category (e.g., Clustering) for the model used for this scoring run.

scoring_time

public long scoring_time

The time in mS since the epoch for the start of this scoring run.

predictions

public FrameV3 predictions

Predictions Frame.

MSE

public double MSE

The Mean Squared Error of the prediction for this scoring run.

Constructor Detail

ModelMetricsGLRMV99

public ModelMetricsGLRMV99()