public class ModelMetricsBaseV3<I extends ModelMetrics,S extends ModelMetricsBaseV3<I,S>> extends SchemaV3<I,S>
SchemaV3.Meta
Modifier and Type | Field and Description |
---|---|
java.lang.String |
description |
KeyV3.FrameKeyV3 |
frame |
long |
frame_checksum |
KeyV3.ModelKeyV3 |
model |
hex.ModelCategory |
model_category |
long |
model_checksum |
double |
MSE |
long |
nobs |
FrameV3 |
predictions |
double |
RMSE |
long |
scoring_time |
Constructor and Description |
---|
ModelMetricsBaseV3() |
ModelMetricsBaseV3(I impl) |
Modifier and Type | Method and Description |
---|---|
S |
fillFromImpl(ModelMetrics modelMetrics)
Fill this Schema from the given implementation object.
|
createAndFillImpl, createImpl, extractVersionFromSchemaName, fillFromImpl, fillFromImpl, fillFromParms, fillFromParms, fillImpl, fillImpl, getImplClass, getImplClass, getSchemaName, getSchemaType, getSchemaVersion, init_meta, markdown, markdown, newInstance, newInstance, setField, setSchemaType_doNotCall
asBytes, clone, copyOver, frozenType, read, readExternal, readJSON, reloadFromBytes, toJsonString, write, writeExternal
@API(help="The model used for this scoring run.", direction=INOUT) public KeyV3.ModelKeyV3 model
@API(help="The checksum for the model used for this scoring run.", direction=INOUT) public long model_checksum
@API(help="The frame used for this scoring run.", direction=INOUT) public KeyV3.FrameKeyV3 frame
@API(help="The checksum for the frame used for this scoring run.", direction=INOUT) public long frame_checksum
@API(help="Optional description for this scoring run (to note out-of-bag, sampled data, etc.)", direction=OUTPUT) public java.lang.String description
@API(help="The category (e.g., Clustering) for the model used for this scoring run.", values={"Unknown","Binomial","Multinomial","Regression","Clustering"}, direction=OUTPUT) public hex.ModelCategory model_category
@API(help="The time in mS since the epoch for the start of this scoring run.", direction=OUTPUT) public long scoring_time
@API(help="The Mean Squared Error of the prediction for this scoring run.", direction=OUTPUT) public double MSE
@API(help="The Root Mean Squared Error of the prediction for this scoring run.", direction=OUTPUT) public double RMSE
public ModelMetricsBaseV3()
public ModelMetricsBaseV3(I impl)
public S fillFromImpl(ModelMetrics modelMetrics)
Schema
fillFromImpl
in class Schema<I extends ModelMetrics,S extends ModelMetricsBaseV3<I,S>>