final class DatasetFeatureStatistics extends GeneratedMessageV3 with DatasetFeatureStatisticsOrBuilder
The feature statistics for a single dataset.
Protobuf type tensorflow.metadata.v0.DatasetFeatureStatistics
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- def getCrossFeatures(index: Int): CrossFeatureStatistics
Cross feature statistics for the dataset.
Cross feature statistics for the dataset.
repeated .tensorflow.metadata.v0.CrossFeatureStatistics cross_features = 5;
- Definition Classes
- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- def getCrossFeaturesCount(): Int
Cross feature statistics for the dataset.
Cross feature statistics for the dataset.
repeated .tensorflow.metadata.v0.CrossFeatureStatistics cross_features = 5;
- Definition Classes
- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- def getCrossFeaturesList(): List[CrossFeatureStatistics]
Cross feature statistics for the dataset.
Cross feature statistics for the dataset.
repeated .tensorflow.metadata.v0.CrossFeatureStatistics cross_features = 5;
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- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- def getCrossFeaturesOrBuilder(index: Int): CrossFeatureStatisticsOrBuilder
Cross feature statistics for the dataset.
Cross feature statistics for the dataset.
repeated .tensorflow.metadata.v0.CrossFeatureStatistics cross_features = 5;
- Definition Classes
- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- @Override()
- def getCrossFeaturesOrBuilderList(): List[_ <: CrossFeatureStatisticsOrBuilder]
Cross feature statistics for the dataset.
Cross feature statistics for the dataset.
repeated .tensorflow.metadata.v0.CrossFeatureStatistics cross_features = 5;
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- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- def getDefaultInstanceForType(): DatasetFeatureStatistics
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- def getFeatures(index: Int): FeatureNameStatistics
The feature statistics for the dataset.
The feature statistics for the dataset.
repeated .tensorflow.metadata.v0.FeatureNameStatistics features = 3;
- Definition Classes
- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- @Override()
- def getFeaturesCount(): Int
The feature statistics for the dataset.
The feature statistics for the dataset.
repeated .tensorflow.metadata.v0.FeatureNameStatistics features = 3;
- Definition Classes
- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- @Override()
- def getFeaturesList(): List[FeatureNameStatistics]
The feature statistics for the dataset.
The feature statistics for the dataset.
repeated .tensorflow.metadata.v0.FeatureNameStatistics features = 3;
- Definition Classes
- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- @Override()
- def getFeaturesOrBuilder(index: Int): FeatureNameStatisticsOrBuilder
The feature statistics for the dataset.
The feature statistics for the dataset.
repeated .tensorflow.metadata.v0.FeatureNameStatistics features = 3;
- Definition Classes
- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
- Annotations
- @Override()
- def getFeaturesOrBuilderList(): List[_ <: FeatureNameStatisticsOrBuilder]
The feature statistics for the dataset.
The feature statistics for the dataset.
repeated .tensorflow.metadata.v0.FeatureNameStatistics features = 3;
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- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- def getName(): String
The name of the dataset.
The name of the dataset.
string name = 1;
- returns
The name.
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- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- def getNameBytes(): ByteString
The name of the dataset.
The name of the dataset.
string name = 1;
- returns
The bytes for name.
- Definition Classes
- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- @Override()
- def getNumExamples(): Long
The number of examples in the dataset.
The number of examples in the dataset.
uint64 num_examples = 2;
- returns
The numExamples.
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- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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- def getParserForType(): Parser[DatasetFeatureStatistics]
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- def getWeightedNumExamples(): Double
Only valid if the weight feature was specified. Treats a missing weighted feature as zero.
Only valid if the weight feature was specified. Treats a missing weighted feature as zero.
double weighted_num_examples = 4;
- returns
The weightedNumExamples.
- Definition Classes
- DatasetFeatureStatistics → DatasetFeatureStatisticsOrBuilder
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