public class ClassificationMetrics
extends java.lang.Object
implements java.io.Serializable
Modifier and Type | Field and Description |
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double |
accuracy
The accuracy on validation data.
|
double |
auc
The AUC on validation data.
|
double |
crossentropy
The cross entropy on validation data.
|
int |
error
The number of errors.
|
double |
f1
The F-1 score on validation data.
|
double |
fitTime
The time in milliseconds of fitting the model.
|
double |
logloss
The log loss on validation data.
|
double |
mcc
The Matthews correlation coefficient on validation data.
|
double |
precision
The precision on validation data.
|
double |
scoreTime
The time in milliseconds of scoring the validation data.
|
double |
sensitivity
The sensitivity on validation data.
|
int |
size
The validation data size.
|
double |
specificity
The specificity on validation data.
|
Constructor and Description |
---|
ClassificationMetrics(double fitTime,
double scoreTime,
int size,
int error,
double accuracy)
Constructor.
|
ClassificationMetrics(double fitTime,
double scoreTime,
int size,
int error,
double accuracy,
double crossentropy)
Constructor of multiclass soft classifier validation.
|
ClassificationMetrics(double fitTime,
double scoreTime,
int size,
int error,
double accuracy,
double sensitivity,
double specificity,
double precision,
double f1,
double mcc)
Constructor of binary classifier validation.
|
ClassificationMetrics(double fitTime,
double scoreTime,
int size,
int error,
double accuracy,
double sensitivity,
double specificity,
double precision,
double f1,
double mcc,
double auc,
double logloss)
Constructor of binary soft classifier validation.
|
ClassificationMetrics(double fitTime,
double scoreTime,
int size,
int error,
double accuracy,
double sensitivity,
double specificity,
double precision,
double f1,
double mcc,
double auc,
double logloss,
double crossentropy)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
java.lang.String |
toString() |
public final double fitTime
public final double scoreTime
public final int size
public final int error
public final double accuracy
public final double sensitivity
public final double specificity
public final double precision
public final double f1
public final double mcc
public final double auc
public final double logloss
public final double crossentropy
public ClassificationMetrics(double fitTime, double scoreTime, int size, int error, double accuracy)
public ClassificationMetrics(double fitTime, double scoreTime, int size, int error, double accuracy, double crossentropy)
public ClassificationMetrics(double fitTime, double scoreTime, int size, int error, double accuracy, double sensitivity, double specificity, double precision, double f1, double mcc)
public ClassificationMetrics(double fitTime, double scoreTime, int size, int error, double accuracy, double sensitivity, double specificity, double precision, double f1, double mcc, double auc, double logloss)
public ClassificationMetrics(double fitTime, double scoreTime, int size, int error, double accuracy, double sensitivity, double specificity, double precision, double f1, double mcc, double auc, double logloss, double crossentropy)