Uses of Class
org.tribuo.multilabel.MultiLabel
Packages that use MultiLabel
Package
Description
Provides an interface to TensorFlow, allowing the training of non-sequential models using any supported
Tribuo output type.
Provides classes and infrastructure for working with multi-label classification problems.
Evaluation classes for multi-label classification using
MultiLabel.Provides a multi-label data generator for testing implementations.
Provides an implementation of a multi-label classification linear model using Stochastic Gradient Descent.
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Uses of MultiLabel in org.tribuo.interop.tensorflow
Classes in org.tribuo.interop.tensorflow that implement interfaces with type arguments of type MultiLabelModifier and TypeClassDescriptionclassCan convert aMultiLabelinto aTensorcontaining a binary encoding of the label vector and can convert aTFloat16orTFloat32into aPredictionor aMultiLabel.Methods in org.tribuo.interop.tensorflow that return MultiLabelModifier and TypeMethodDescriptionMultiLabelConverter.convertToOutput(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo) Methods in org.tribuo.interop.tensorflow that return types with arguments of type MultiLabelModifier and TypeMethodDescriptionMultiLabelConverter.convertToBatchOutput(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo) MultiLabelConverter.convertToBatchPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo, int[] numValidFeatures, List<Example<MultiLabel>> examples) MultiLabelConverter.convertToPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo, int numValidFeatures, Example<MultiLabel> example) Methods in org.tribuo.interop.tensorflow with parameters of type MultiLabelModifier and TypeMethodDescriptionorg.tensorflow.TensorMultiLabelConverter.convertToTensor(MultiLabel example, ImmutableOutputInfo<MultiLabel> outputIDInfo) Method parameters in org.tribuo.interop.tensorflow with type arguments of type MultiLabelModifier and TypeMethodDescriptionMultiLabelConverter.convertToBatchOutput(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo) MultiLabelConverter.convertToBatchPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo, int[] numValidFeatures, List<Example<MultiLabel>> examples) MultiLabelConverter.convertToBatchPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo, int[] numValidFeatures, List<Example<MultiLabel>> examples) MultiLabelConverter.convertToOutput(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo) MultiLabelConverter.convertToPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo, int numValidFeatures, Example<MultiLabel> example) MultiLabelConverter.convertToPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo, int numValidFeatures, Example<MultiLabel> example) org.tensorflow.TensorMultiLabelConverter.convertToTensor(List<Example<MultiLabel>> examples, ImmutableOutputInfo<MultiLabel> outputIDInfo) org.tensorflow.TensorMultiLabelConverter.convertToTensor(List<Example<MultiLabel>> examples, ImmutableOutputInfo<MultiLabel> outputIDInfo) org.tensorflow.TensorMultiLabelConverter.convertToTensor(MultiLabel example, ImmutableOutputInfo<MultiLabel> outputIDInfo) -
Uses of MultiLabel in org.tribuo.multilabel
Classes in org.tribuo.multilabel that implement interfaces with type arguments of type MultiLabelModifier and TypeClassDescriptionclassAn ImmutableOutputInfo for working with multi-label tasks.classA class for multi-label classification.final classA factory for generating MultiLabel objects and their associated OutputInfo and Evaluator objects.classThe base class for information aboutMultiLabeloutputs.classA MutableOutputInfo for working with multi-label tasks.Fields in org.tribuo.multilabel declared as MultiLabelFields in org.tribuo.multilabel with type parameters of type MultiLabelMethods in org.tribuo.multilabel that return MultiLabelModifier and TypeMethodDescriptionMultiLabel.copy()static MultiLabelMultiLabel.createFromPairList(List<com.oracle.labs.mlrg.olcut.util.Pair<String, Boolean>> dimensions) Creates a MultiLabel from a list of dimensions.<V> MultiLabelMultiLabelFactory.generateOutput(V label) Parses the MultiLabel value either by toStringing the input and callingparseString(java.lang.String)or if it's aCollectioniterating over the elements calling toString on each element in turn and usingparseElement(java.lang.String).ImmutableMultiLabelInfo.getOutput(int id) MultiLabelFactory.getUnknownOutput()static MultiLabelMultiLabel.parseString(String s) Parses a string of the form: dimension-name=output,...,dimension-name=output where output must be readable byBoolean.parseBoolean(String).static MultiLabelMultiLabel.parseString(String s, char splitChar) Parses a string of the form:Methods in org.tribuo.multilabel that return types with arguments of type MultiLabelModifier and TypeMethodDescriptionMultiLabelFactory.constructInfoForExternalModel(Map<MultiLabel, Integer> mapping) MultiLabelInfo.generateImmutableOutputInfo()MultiLabelFactory.generateInfo()MultiLabelInfo.generateMutableOutputInfo()ImmutableMultiLabelInfo.getDomain()MultiLabelInfo.getDomain()Returns a set of MultiLabel, where each has a single Label inside it.MultiLabelFactory.getEvaluator()Iterator<com.oracle.labs.mlrg.olcut.util.Pair<Integer, MultiLabel>> ImmutableMultiLabelInfo.iterator()Methods in org.tribuo.multilabel with parameters of type MultiLabelModifier and TypeMethodDescriptionbooleanMultiLabel.fullEquals(MultiLabel o) intImmutableMultiLabelInfo.getID(MultiLabel output) static intMultiLabel.intersectionSize(MultiLabel first, MultiLabel second) The number of labels present in both MultiLabels.static doubleMultiLabel.jaccardScore(MultiLabel first, MultiLabel second) The Jaccard score/index between the two MultiLabels.voidMutableMultiLabelInfo.observe(MultiLabel output) Throws IllegalStateException if the MultiLabel contains a Label which has a "," in it.static intMultiLabel.unionSize(MultiLabel first, MultiLabel second) The number of unique labels across both MultiLabels.Method parameters in org.tribuo.multilabel with type arguments of type MultiLabelModifier and TypeMethodDescriptionMultiLabelFactory.constructInfoForExternalModel(Map<MultiLabel, Integer> mapping) MultiLabel.convertToDenseVector(ImmutableOutputInfo<MultiLabel> info) Converts this MultiLabel into a DenseVector using the indices from the output info.MultiLabel.convertToSparseVector(ImmutableOutputInfo<MultiLabel> info) Converts this MultiLabel into a SparseVector using the indices from the output info. -
Uses of MultiLabel in org.tribuo.multilabel.baseline
Subclasses with type arguments of type MultiLabel in org.tribuo.multilabel.baselineModifier and TypeClassDescriptionclassAModelwhich wraps n binary models, where n is the size of the MultiLabel domain.Classes in org.tribuo.multilabel.baseline that implement interfaces with type arguments of type MultiLabelModifier and TypeClassDescriptionclassMethods in org.tribuo.multilabel.baseline that return types with arguments of type MultiLabelModifier and TypeMethodDescriptionIndependentMultiLabelModel.getExcuse(Example<MultiLabel> example) IndependentMultiLabelModel.predict(Example<MultiLabel> example) IndependentMultiLabelTrainer.train(Dataset<MultiLabel> examples, Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance) Method parameters in org.tribuo.multilabel.baseline with type arguments of type MultiLabelModifier and TypeMethodDescriptionIndependentMultiLabelModel.getExcuse(Example<MultiLabel> example) IndependentMultiLabelModel.predict(Example<MultiLabel> example) IndependentMultiLabelTrainer.train(Dataset<MultiLabel> examples, Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance) -
Uses of MultiLabel in org.tribuo.multilabel.evaluation
Subclasses with type arguments of type MultiLabel in org.tribuo.multilabel.evaluationSubinterfaces with type arguments of type MultiLabel in org.tribuo.multilabel.evaluationClasses in org.tribuo.multilabel.evaluation that implement interfaces with type arguments of type MultiLabelModifier and TypeClassDescriptionfinal classAConfusionMatrixwhich acceptsMultiLabels.classAEvaluationMetricfor evaluatingMultiLabelproblems.Methods in org.tribuo.multilabel.evaluation that return types with arguments of type MultiLabelModifier and TypeMethodDescriptionMultiLabelEvaluationImpl.asMap()MultiLabelEvaluationImpl.getConfusionMatrix()MultiLabelConfusionMatrix.getDomain()BiFunction<MetricTarget<MultiLabel>, org.tribuo.multilabel.evaluation.MultiLabelMetric.Context, Double> MultiLabelMetrics.getImpl()Get the implementation function for this metric.MultiLabelEvaluationImpl.getPredictions()MultiLabelMetric.getTarget()Methods in org.tribuo.multilabel.evaluation with parameters of type MultiLabelModifier and TypeMethodDescriptiondoubleMultiLabelConfusionMatrix.confusion(MultiLabel predicted, MultiLabel truth) doubleMultiLabelEvaluationImpl.confusion(MultiLabel predicted, MultiLabel truth) doubleMultiLabelEvaluationImpl.f1(MultiLabel label) doubleMultiLabelConfusionMatrix.fn(MultiLabel cls) doubleMultiLabelEvaluationImpl.fn(MultiLabel label) doubleMultiLabelConfusionMatrix.fp(MultiLabel cls) doubleMultiLabelEvaluationImpl.fp(MultiLabel label) doubleMultiLabelEvaluationImpl.precision(MultiLabel label) doubleMultiLabelEvaluationImpl.recall(MultiLabel label) doubleMultiLabelConfusionMatrix.support(MultiLabel cls) doubleMultiLabelConfusionMatrix.tn(MultiLabel cls) doubleMultiLabelEvaluationImpl.tn(MultiLabel label) doubleMultiLabelConfusionMatrix.tp(MultiLabel cls) doubleMultiLabelEvaluationImpl.tp(MultiLabel label) Method parameters in org.tribuo.multilabel.evaluation with type arguments of type MultiLabelModifier and TypeMethodDescriptionprotected org.tribuo.multilabel.evaluation.MultiLabelMetric.ContextMultiLabelEvaluator.createContext(Model<MultiLabel> model, List<Prediction<MultiLabel>> predictions) protected org.tribuo.multilabel.evaluation.MultiLabelMetric.ContextMultiLabelEvaluator.createContext(Model<MultiLabel> model, List<Prediction<MultiLabel>> predictions) org.tribuo.multilabel.evaluation.MultiLabelMetric.ContextMultiLabelMetric.createContext(Model<MultiLabel> model, List<Prediction<MultiLabel>> predictions) org.tribuo.multilabel.evaluation.MultiLabelMetric.ContextMultiLabelMetric.createContext(Model<MultiLabel> model, List<Prediction<MultiLabel>> predictions) protected MultiLabelEvaluationMultiLabelEvaluator.createEvaluation(org.tribuo.multilabel.evaluation.MultiLabelMetric.Context context, Map<MetricID<MultiLabel>, Double> results, EvaluationProvenance provenance) protected Set<MultiLabelMetric> MultiLabelEvaluator.createMetrics(Model<MultiLabel> model) MultiLabelMetrics.forTarget(MetricTarget<MultiLabel> tgt) Get the metric for the supplied target.doubleMultiLabelEvaluationImpl.get(MetricID<MultiLabel> key) static doubleMultiLabelMetrics.jaccardScore(List<Prediction<MultiLabel>> predictions) The average Jaccard score across the predictions.Constructor parameters in org.tribuo.multilabel.evaluation with type arguments of type MultiLabelModifierConstructorDescriptionMultiLabelConfusionMatrix(Model<MultiLabel> model, List<Prediction<MultiLabel>> predictions) MultiLabelConfusionMatrix(Model<MultiLabel> model, List<Prediction<MultiLabel>> predictions) MultiLabelMetric(MetricTarget<MultiLabel> target, String name, BiFunction<MetricTarget<MultiLabel>, org.tribuo.multilabel.evaluation.MultiLabelMetric.Context, Double> impl) MultiLabelMetric(MetricTarget<MultiLabel> target, String name, BiFunction<MetricTarget<MultiLabel>, org.tribuo.multilabel.evaluation.MultiLabelMetric.Context, Double> impl) -
Uses of MultiLabel in org.tribuo.multilabel.example
Methods in org.tribuo.multilabel.example that return types with arguments of type MultiLabelModifier and TypeMethodDescriptionstatic Example<MultiLabel> MultiLabelDataGenerator.emptyExample()Generates an example with no features.static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<MultiLabel>, Dataset<MultiLabel>> MultiLabelDataGenerator.generateDataset()static com.oracle.labs.mlrg.olcut.util.Pair<Dataset<MultiLabel>, Dataset<MultiLabel>> MultiLabelDataGenerator.generateDataset()static Dataset<MultiLabel> MultiLabelDataGenerator.generateTestData()static Dataset<MultiLabel> MultiLabelDataGenerator.generateTrainData()static Example<MultiLabel> MultiLabelDataGenerator.invalidSparseExample()Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class. -
Uses of MultiLabel in org.tribuo.multilabel.sgd.linear
Subclasses with type arguments of type MultiLabel in org.tribuo.multilabel.sgd.linearModifier and TypeClassDescriptionclassThe inference time version of a multi-label linear model trained using SGD.classA trainer for a multi-label linear model which uses SGD.Methods in org.tribuo.multilabel.sgd.linear that return types with arguments of type MultiLabelMethods in org.tribuo.multilabel.sgd.linear with parameters of type MultiLabelModifier and TypeMethodDescriptionprotected SparseVectorLinearSGDTrainer.getTarget(ImmutableOutputInfo<MultiLabel> outputInfo, MultiLabel output) Method parameters in org.tribuo.multilabel.sgd.linear with type arguments of type MultiLabelModifier and TypeMethodDescriptionprotected LinearSGDModelLinearSGDTrainer.createModel(String name, ModelProvenance provenance, ImmutableFeatureMap featureMap, ImmutableOutputInfo<MultiLabel> outputInfo, LinearParameters parameters) protected SparseVectorLinearSGDTrainer.getTarget(ImmutableOutputInfo<MultiLabel> outputInfo, MultiLabel output) LinearSGDModel.predict(Example<MultiLabel> example)