@Generated(value="OracleSDKGenerator", comments="API Version: 20221001") public final class ClassMetrics extends com.oracle.bmc.http.client.internal.ExplicitlySetBmcModel
class level Text Classification model metrics
Note: Objects should always be created or deserialized using the ClassMetrics.Builder
. This model
distinguishes fields that are null
because they are unset from fields that are explicitly
set to null
. This is done in the setter methods of the ClassMetrics.Builder
, which maintain a
set of all explicitly set fields called ClassMetrics.Builder.__explicitlySet__
. The hashCode()
and equals(Object)
methods are implemented to take the explicitly set
fields into account. The constructor, on the other hand, does not take the explicitly set fields
into account (since the constructor cannot distinguish explicit null
from unset null
).
Modifier and Type | Class and Description |
---|---|
static class |
ClassMetrics.Builder |
EXPLICITLY_SET_FILTER_NAME, EXPLICITLY_SET_PROPERTY_NAME
Constructor and Description |
---|
ClassMetrics(String label,
Float f1,
Float precision,
Float recall,
Float support)
Deprecated.
|
Modifier and Type | Method and Description |
---|---|
static ClassMetrics.Builder |
builder()
Create a new builder.
|
boolean |
equals(Object o) |
Float |
getF1()
F1-score, is a measure of a model’s accuracy on a dataset
|
String |
getLabel()
Text classification label
|
Float |
getPrecision()
Precision refers to the number of true positives divided by the total number of positive
predictions (i.e., the number of true positives plus the number of false positives)
|
Float |
getRecall()
Measures the model’s ability to predict actual positive classes.
|
Float |
getSupport()
number of samples in the test set
|
int |
hashCode() |
ClassMetrics.Builder |
toBuilder() |
String |
toString() |
String |
toString(boolean includeByteArrayContents)
Return a string representation of the object.
|
markPropertyAsExplicitlySet, wasPropertyExplicitlySet
@Deprecated @ConstructorProperties(value={"label","f1","precision","recall","support"}) public ClassMetrics(String label, Float f1, Float precision, Float recall, Float support)
public static ClassMetrics.Builder builder()
Create a new builder.
public ClassMetrics.Builder toBuilder()
public String getLabel()
Text classification label
public Float getF1()
F1-score, is a measure of a model’s accuracy on a dataset
public Float getPrecision()
Precision refers to the number of true positives divided by the total number of positive predictions (i.e., the number of true positives plus the number of false positives)
public Float getRecall()
Measures the model’s ability to predict actual positive classes. It is the ratio between the predicted true positives and what was actually tagged. The recall metric reveals how many of the predicted classes are correct.
public Float getSupport()
number of samples in the test set
public String toString()
toString
in class com.oracle.bmc.http.client.internal.ExplicitlySetBmcModel
public String toString(boolean includeByteArrayContents)
Return a string representation of the object.
includeByteArrayContents
- true to include the full contents of byte arrayspublic boolean equals(Object o)
equals
in class com.oracle.bmc.http.client.internal.ExplicitlySetBmcModel
public int hashCode()
hashCode
in class com.oracle.bmc.http.client.internal.ExplicitlySetBmcModel
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