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MicrosoftResearch.Infer.Learners Namespace
Microsoft Research
Infer.NET learners
Classes
  ClassDescription
Public classBayesPointMachineClassifier
The Bayes point machine classifier factory.
Public classBayesPointMachineClassifierCapabilities
Defines the capabilities of the Bayes point machine classifier.
Public classBayesPointMachineClassifierException
The exception that is thrown when the multi-class Bayes point machine classifier encounters an issue.
Public classBayesPointMachineClassifierIterationChangedEventArgs
Provides information about the training progress of the Bayes point machine classifiers.
Public classBayesPointMachineClassifierPredictionSettingsTLabel
Abstract prediction settings of a Bayes point machine classifier.
Public classBayesPointMachineClassifierSettingsTLabel, TTrainingSettings, TPredictionSettings
Abstract settings of the Bayes point machine classifier.
Public classBayesPointMachineClassifierTrainingSettings
Settings for the Bayes point machine classifier which affect training.
Public classBinaryBayesPointMachineClassifierPredictionSettingsTLabel
Settings for the binary Bayes point machine classifier which affect prediction.
Public classBinaryBayesPointMachineClassifierSettingsTLabel
Settings of the binary Bayes point machine classifier.
Public classClassifierEvaluatorTInstanceSource, TInstance, TLabelSource, TLabel
Evaluates the predictions of a classifier.
Public classConfusionMatrixTLabel
Implements a confusion matrix.
Public classDummyFeatureSource
Indicates that no explicit feature source is needed because features are implicitly stored somewhere else.
Public classMatchboxRecommender
Matchbox recommender factory.
Public classMatchboxRecommenderAdvancedTrainingSettings
Advanced settings of the Matchbox recommender which affect training. Cannot be set after training.
Public classMatchboxRecommenderCapabilities
Defines the capabilities of the Matchbox recommender.
Public classMatchboxRecommenderException
The exception that is thrown in the case of some issues encountered by the recommendation engine.
Public classMatchboxRecommenderPredictionSettings
Settings of the Matchbox recommender which affect prediction.
Public classMatchboxRecommenderSettings
Settings of the Matchbox recommender (settable by the developer).
Public classMatchboxRecommenderTrainingSettings
Settings of the Matchbox recommender which affect training. Cannot be set after training.
Public classMetrics
A diverse set of metrics to evaluate various kinds of predictors.
Public classMulticlassBayesPointMachineClassifierPredictionSettingsTLabel
Settings for the multi-class Bayes point machine classifier which affect prediction.
Public classMulticlassBayesPointMachineClassifierSettingsTLabel
Settings of the multi-class Bayes point machine classifier.
Public classNoFeatureSource
Indicates that no feature source is needed because the model does not use features.
Public classPointEstimator
Implements point estimators.
Public classRandomStarRatingRecommenderTInstanceSource, TInstance, TUser, TItem, TDataRating, TFeatureSource, TFeatureValues
Represents a star rating recommender system which generates predictions purely by random guessing.
Public classRandomStarRatingRecommenderCapabilities
Defines the capabilities of the Matchbox recommender.
Public classRatingInstanceTUser, TItem, TRating
Represents a user-item-rating triple.
Public classRatingMatrix
Represents a matrix of values for predicted ratings versus true ratings. Usages include a confusion matrix and a loss matrix.
Public classRecommenderEvaluatorTInstanceSource, TUser, TItem, TGroundTruthRating, TPredictedRating, TPredictedRatingDist
Evaluates a recommender system.
Public classRoundingStarRatingInfo
Public classSerializationUtils
Implements various utilities related to learner serialization.
Public classSerializationVersionAttribute
Sets the serialization version of the learner.
Public classSettingsGuard
Guards settings from being changed.
Public classStarRatingInfo
Provides a mapping for the case in which ratings are already star ratings.
Public classStarRatingRecommenderEvaluatorTInstanceSource, TUser, TItem, TGroundTruthRating
Evaluates a recommender system which predicts star ratings.
Interfaces
  InterfaceDescription
Public interfaceIBayesPointMachineClassifierTInstanceSource, TInstance, TLabelSource, TLabel, TLabelDistribution, TTrainingSettings, TPredictionSettings
Interface to a Bayes point machine classifier.
Public interfaceIBayesPointMachineClassifierPredictionSettingsTLabel
Interface to prediction settings of a Bayes point machine classifier.
Public interfaceIBayesPointMachineClassifierSettingsTLabel, TTrainingSettings, TPredictionSettings
Interface to settings of a Bayes point machine classifier.
Public interfaceICapabilities
Interface to learner capabilities.
Public interfaceILearner
Interface to a learner (something that can do machine learning).
Public interfaceIMatchboxRecommenderTInstanceSource, TUser, TItem, TFeatureSource
Interface to a Matchbox recommender system.
Public interfaceIPredictorTInstanceSource, TInstance, TLabelSource, TResult, TResultDist
Interface to a learner that acts on some data to predict a label.
Public interfaceIPredictorCapabilities
Interface to predictor capabilities.
Public interfaceIPredictorIncrementalTrainingTInstanceSource, TLabelSource
Interface to a predictor which can be trained incrementally.
Public interfaceIRecommenderTInstanceSource, TUser, TItem, TRating, TRatingDist, TFeatureSource
Interface to a recommendation algorithm.
Public interfaceIRecommenderCapabilities
Interface to a recommender capabilities.
Public interfaceISettings
Interface to the settings of an implementation of ILearner. These should be set once to configure the learner before calling any query methods on it.
Public interfaceIStarRatingInfoTRating
Interface to provide a mapping from ratings of arbitrary type TRating to star ratings.
Enumerations
  EnumerationDescription
Public enumerationLossFunction
The loss function which determines how a prediction in the form of a distribution is converted into a point prediction.
Public enumerationRecommenderMetricAggregationMethod
Specifies how metrics are aggregated over the whole dataset.