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public static interface ModelEvaluation.BiasConfigOrBuilder extends MessageOrBuilder
Implements
MessageOrBuilderMethods
getBiasSlices()
public abstract ModelEvaluationSlice.Slice.SliceSpec getBiasSlices()
Specification for how the data should be sliced for bias. It contains a list of slices, with limitation of two slices. The first slice of data will be the slice_a. The second slice in the list (slice_b) will be compared against the first slice. If only a single slice is provided, then slice_a will be compared against "not slice_a". Below are examples with feature "education" with value "low", "medium", "high" in the dataset:
Example 1:
bias_slices = [{'education': 'low'}]
A single slice provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'medium' or 'high'.
Example 2:
bias_slices = [{'education': 'low'},
{'education': 'high'}]
Two slices provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'high'.
.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;
Returns | |
---|---|
Type | Description |
ModelEvaluationSlice.Slice.SliceSpec | The biasSlices. |
getBiasSlicesOrBuilder()
public abstract ModelEvaluationSlice.Slice.SliceSpecOrBuilder getBiasSlicesOrBuilder()
Specification for how the data should be sliced for bias. It contains a list of slices, with limitation of two slices. The first slice of data will be the slice_a. The second slice in the list (slice_b) will be compared against the first slice. If only a single slice is provided, then slice_a will be compared against "not slice_a". Below are examples with feature "education" with value "low", "medium", "high" in the dataset:
Example 1:
bias_slices = [{'education': 'low'}]
A single slice provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'medium' or 'high'.
Example 2:
bias_slices = [{'education': 'low'},
{'education': 'high'}]
Two slices provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'high'.
.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;
Returns | |
---|---|
Type | Description |
ModelEvaluationSlice.Slice.SliceSpecOrBuilder |
getLabels(int index)
public abstract String getLabels(int index)
Positive labels selection on the target field.
repeated string labels = 2;
Parameter | |
---|---|
Name | Description |
index | int The index of the element to return. |
Returns | |
---|---|
Type | Description |
String | The labels at the given index. |
getLabelsBytes(int index)
public abstract ByteString getLabelsBytes(int index)
Positive labels selection on the target field.
repeated string labels = 2;
Parameter | |
---|---|
Name | Description |
index | int The index of the value to return. |
Returns | |
---|---|
Type | Description |
ByteString | The bytes of the labels at the given index. |
getLabelsCount()
public abstract int getLabelsCount()
Positive labels selection on the target field.
repeated string labels = 2;
Returns | |
---|---|
Type | Description |
int | The count of labels. |
getLabelsList()
public abstract List<String> getLabelsList()
Positive labels selection on the target field.
repeated string labels = 2;
Returns | |
---|---|
Type | Description |
List<String> | A list containing the labels. |
hasBiasSlices()
public abstract boolean hasBiasSlices()
Specification for how the data should be sliced for bias. It contains a list of slices, with limitation of two slices. The first slice of data will be the slice_a. The second slice in the list (slice_b) will be compared against the first slice. If only a single slice is provided, then slice_a will be compared against "not slice_a". Below are examples with feature "education" with value "low", "medium", "high" in the dataset:
Example 1:
bias_slices = [{'education': 'low'}]
A single slice provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'medium' or 'high'.
Example 2:
bias_slices = [{'education': 'low'},
{'education': 'high'}]
Two slices provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'high'.
.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;
Returns | |
---|---|
Type | Description |
boolean | Whether the biasSlices field is set. |