final class MultiLabelClassification extends GeneratedMessageV3 with MultiLabelClassificationOrBuilder
Configuration for a multi-label classification task. In this problem type there are n_classes unique possible label values overall. There can be from zero up to n_classes unique labels per example. The output, which is of type real number, is class probabilities associated with each class. It will be of n_classes dimension for each example, if n_classes is specified. Otherwise, the dimension will be set to the number of unique class labels that are dynamically inferred from the data based on dynamic_class_spec.
Protobuf type tensorflow.metadata.v0.MultiLabelClassification
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- def getClassSpecCase(): ClassSpecCase
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- MultiLabelClassification → MultiLabelClassificationOrBuilder
- def getDefaultInstanceForType(): MultiLabelClassification
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- def getDescriptorForType(): Descriptor
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- def getDynamicClassSpec(): DynamicClassSpec
The maximal number of label classes that should be inferred dynamically from the data.
The maximal number of label classes that should be inferred dynamically from the data.
.tensorflow.metadata.v0.DynamicClassSpec dynamic_class_spec = 4;- returns
The dynamicClassSpec.
- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
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- @Override()
- def getDynamicClassSpecOrBuilder(): DynamicClassSpecOrBuilder
The maximal number of label classes that should be inferred dynamically from the data.
The maximal number of label classes that should be inferred dynamically from the data.
.tensorflow.metadata.v0.DynamicClassSpec dynamic_class_spec = 4;- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
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- @Override()
- def getExampleWeight(): String
The weight column.
The weight column.
string example_weight = 2;- returns
The exampleWeight.
- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
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- @Override()
- def getExampleWeightBytes(): ByteString
The weight column.
The weight column.
string example_weight = 2;- returns
The bytes for exampleWeight.
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- def getField(field: FieldDescriptor): AnyRef
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- def getInitializationErrorString(): String
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- def getLabel(): String
The name of the label. Assumes the label is a flat, top-level field.
The name of the label. Assumes the label is a flat, top-level field.
string label = 1;- returns
The label.
- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
- def getLabelBytes(): ByteString
The name of the label. Assumes the label is a flat, top-level field.
The name of the label. Assumes the label is a flat, top-level field.
string label = 1;- returns
The bytes for label.
- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
- def getLabelIdCase(): LabelIdCase
- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
- def getLabelPath(): Path
A path can be used instead of a flat string if the label is nested.
A path can be used instead of a flat string if the label is nested.
.tensorflow.metadata.v0.Path label_path = 5;- returns
The labelPath.
- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
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- @Override()
- def getLabelPathOrBuilder(): PathOrBuilder
A path can be used instead of a flat string if the label is nested.
A path can be used instead of a flat string if the label is nested.
.tensorflow.metadata.v0.Path label_path = 5;- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
- Annotations
- @Override()
- def getNClasses(): Long
The exact number of unique class labels.
The exact number of unique class labels.
uint64 n_classes = 3;- returns
The nClasses.
- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
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- @Override()
- def getOneofFieldDescriptor(oneof: OneofDescriptor): FieldDescriptor
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- def getParserForType(): Parser[MultiLabelClassification]
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- def getRepeatedField(field: FieldDescriptor, index: Int): AnyRef
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- def getRepeatedFieldCount(field: FieldDescriptor): Int
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- def getSerializedSize(): Int
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- def getUnknownFields(): UnknownFieldSet
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- def hasDynamicClassSpec(): Boolean
The maximal number of label classes that should be inferred dynamically from the data.
The maximal number of label classes that should be inferred dynamically from the data.
.tensorflow.metadata.v0.DynamicClassSpec dynamic_class_spec = 4;- returns
Whether the dynamicClassSpec field is set.
- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
- Annotations
- @Override()
- def hasField(field: FieldDescriptor): Boolean
- Definition Classes
- GeneratedMessageV3 → MessageOrBuilder
- def hasLabel(): Boolean
The name of the label. Assumes the label is a flat, top-level field.
The name of the label. Assumes the label is a flat, top-level field.
string label = 1;- returns
Whether the label field is set.
- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
- def hasLabelPath(): Boolean
A path can be used instead of a flat string if the label is nested.
A path can be used instead of a flat string if the label is nested.
.tensorflow.metadata.v0.Path label_path = 5;- returns
Whether the labelPath field is set.
- Definition Classes
- MultiLabelClassification → MultiLabelClassificationOrBuilder
- Annotations
- @Override()
- def hasNClasses(): Boolean
The exact number of unique class labels.
The exact number of unique class labels.
uint64 n_classes = 3;- returns
Whether the nClasses field is set.
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- MultiLabelClassification → MultiLabelClassificationOrBuilder
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