All Classes

Class	Description
AbstractQlt<T extends com.tibco.patterns.learn.jaxb.model.SearchQueryBaseType>	Stores a single querylet in an XML structure.
AddPairsResult	Contains sets of pairs that were added to each dataset, and collections of pairs that were not added to the project for various reasons.
COErrorRate	Stops the training when the error rate over validation dataset during the last iteration is below the given threshold.
COErrorRate.IterationResult	Stores statistics for a full or partial training iteration
COErrorRateMin	Stops the training after a minimum error rate for the validation dataset was found and this result was not improved during the specified number of subsequent iterations.
CognateQlt	A Cognate querylet for matching several related text fields where values may be entered into a wrong field.
COIterationCount	A simple class that counts iterations and stops training after the given maximum number of iterations has been reached.
ConfDefault	Settings for the default model confidence measure.
ConfFeature	Feature based confidence measure.
Confidence	Defines a confidence measure and its options.
ConfNone	Turns off calculation of a confidence measure.
ConfQFeature	Extends the ConfFeature class to provide means to configure a NetricsQuery.
ConfQNone	Extends the ConfNone class to provide means to configure a NetricsQuery.
ConfQuery	Defines a confidence measure that can be used in a Patterns server RLink query.
ConfRatio	Weighted true/false ratio confidence measure.
ConfRatioLabel	Label based confidence measure.
ConfStats	Confidence measure based on submodel statistics.
ConvergenceObserver	Defines an object that makes decisions when to stop the training.
COScoreChange	Stops the training when the maximum change in prediction scores compared with the previous iteration is below the given threshold.
DataPartition	Defines the type of a dataset: Training, Validation, Test, Reserve, Low Confidence, False Subsets.
DatasetResult	Stores model training results for one dataset.
DatasetStats	Stores statistics about existing pairs in a dataset, grouped by subset: the number of pairs with each label and the total number of labeled pairs.
DateQlt	A Date querylet for comparing the similarity of date values.
Feature<T extends com.tibco.patterns.learn.jaxb.model.FeatureType>	A user-defined feature composed of one or more querylets.
FeatureListener	Classes implementing this interface receive notifications when feature query changes.
FeatureQuery	Supports a feature query that can contain all types of features.
FeatureVector	Stores a feature vector that can be predicted by a Learn model.
FieldStats	Stores statistics for one table field.
GenderFeature	A feature with 2 predicate querylets that mean: both records are male; both records are female.
GenericFeature	A generic feature that has a single querylet of any type.
Hint	Any suggestion that is given to the user based on the current state of the project.
HintAddLabel	Hint to add pairs for subsets that have too few True/False labels.
HintAddPairs	A hint to select additional record pairs for specified subsets.
HintAddUnderrepr	Hint to add pairs to subsets that are underrepresented in training dataset.
HintAddUntrained	Hint to add pairs to subsets that are present in validation dataset, but are not in training dataset.
HintAddUntrainedInTable	Hint to add pairs to subsets that are not found in either training or validation datasets, but are found in the data table.
HintReviewContra	A hint to review pairs that have contradicting pairs.
HintReviewMislabeled	A hint to review possibly mislabeled pairs.
HintReviewPairs	A hint to review the labels for a list of existing record pairs.
LowConfPairFinder	Finds new low confidence pairs to be labeled and added to the project.
ModelConfig	Stores a configuration of an RLink model and builds model(s) with this configuration.
ModelSettings	Stores all settings for a single Patterns Learn model.xml file.
ModelTrainConfig	Defines configuration for creating and training a Learn model.
ModelTrainer	Functionality to communicate with Patterns server, load data table, calculate feature scores, train and evaluate model.
Partition	Defines the type of a dataset: Training or Validation.
PersonNameFeature	A feature with 3 querylets: Simple: first name, with thesaurus; Simple: last name; Cognate: first, middle (optional) and last name fields, with thesaurus, non-cognate weight 0.8, empty field penalty 0.1.
PredicateQlt	A Predicate querylet for evaluating a predicate expression.
PredictOptions	Holds all options for calculating prediction using a Learn model.
ProjectFiles	Manages all files for one Patterns Learn project.
ProjectSettings	Stores all settings for a single Patterns Learn project.xml file.
Querylet	Defines shared functionality for a single Learn querylet.
RecPair	Stores information about one record pair, including field values, feature scores and label.
RecPair.ConfScoreComparator	Provides ordering by a combination (weighted sum) of the prediction confidence (ascending) and the distance of the model score from the 0.5 threshold (ascending).
RecPair.Label	Defines a label that can be assigned to a record pair: True, False or Unsure.
RecPairExample	A training example constructed based on a pair of database records.
RecPairExperiment	Manages a training dataset and a validation dataset.
RecPairId	Stores a pair of keys.
RecPairMap	Manages datasets in the XML structure in sync with a map of all record pairs that are stored in these datasets.
RecPairScorer	Manages calculation of feature scores and communication with Patterns server.
RecPairSet	A container for storing a set of RecPairExample training examples.
RLink	Performs communication with rlink_jni library using JNI to create, load, save, train and evaluate RLink models.
RLink.SubsetTrainMode	Defines methods used to generate training examples for subsets of given training example
RLink.ThermometerType	Type of thermometers used in RLink model.
RLinkDataSet<T extends VectorExample>	A container for storing a set of training examples suitable for model training.
RLinkExperiment<T extends VectorExample>	Manages all data required for a model training experiment: training and validation datasets.
RLinkOut	Stores the result of RLink model prediction.
RLinkServerInterface	Provides more convenient communication with the Patterns server in situations that are frequently used in record pair scoring for Learn.
SimpleQlt	A Simple querylet for matching one field or concatenated string values of several fields.
STAll	Specifies training of all subsets with generated examples.
STDynamic	Specifies dynamic training of subsets.
STFixed	Specifies training up to a fixed depth of subsets, defined by percentage of missing information in the subset.
STNone	Specifies training with actual examples only, without any generated examples for submodels.
STTaper	Specifies the use of a random tapering function to generate some examples for subsets.
SubsetFamily	Stores a family (a set) of RLink subsets.
SubsetLabelPairMap	Stores a family (a set) of RLink subsets.
SubsetTrainConfig	Defines configuration parameters for one of the subset training modes.
TextQlt<T extends com.tibco.patterns.learn.jaxb.model.SearchQueryBaseType>	Provides common functionality for querylets that use approximate text matching (Simple and Cognate querylets).
ThermoCsvDump	Dumps thermometers to CSV files
Thesaurus	Represents thesaurus file that can be used in multiple querylets.
Thesaurus.Type	The type of a thesaurus file.
Trainer	Implements automated training for a single RLink model.
TrainingObserver	Defines an object that gathers training statistics for a certain dataset.
ValueFreq	Stores one field value and its frequency.
VectorExample	Stores a feature vector and a label that are used for training the model.
VectorExperiment	Manages a training dataset and a validation dataset.
VectorSet	A container for storing a set of VectorExample training examples.