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Class Summary |
| AbstractInstance |
Common code for all instance implementations |
| BasicDataset |
A set of examples for learning. |
| BasicDataset.SimpleDatasetViewer |
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| BasicFeatureIndex |
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| BatchBinaryClassifierLearner |
Simple abstract class, getBinaryClassifier() method for a
BinaryClassifierLearner, and also a batchTrainBinary() method. |
| BatchClassifierLearner |
Abstract ClassifierLearner which instantiates the teacher-learner protocol
so as to implement a standard batch learner. |
| BatchVersion |
Batch version of an OnlineClassifierLearner. |
| BinaryBatchVersion |
Batch version of an OnlineBinaryClassifierLearner |
| BinaryClassifier |
A Classifier which associates instances with a real number. |
| CascadingBinaryLearner |
Multi-class version of a binary classifier. |
| ClassifierLearnerFactory |
Generate many copies of a ClassifierLearner. |
| ClassifierTeacher |
Implements the teacher's side of the learner-teacher protocol. |
| ClassifyCommandLineUtil |
Main UI program for the 'classify' package. |
| ClassifyCommandLineUtil.BaseParams |
Parameters used for all experiments |
| ClassifyCommandLineUtil.Learner |
Generalized class for Leaner... |
| ClassifyCommandLineUtil.Learner.ClassifierLearner |
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| ClassifyCommandLineUtil.Learner.SequentialLearner |
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| ClassifyCommandLineUtil.MultiTestParams |
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| ClassifyCommandLineUtil.MultiTrainParams |
Paramaters for training with a simple dataset |
| ClassifyCommandLineUtil.MultiTrainTestParams |
Specific TrainTestParameters for Multi mode. |
| ClassifyCommandLineUtil.SeqTestParams |
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| ClassifyCommandLineUtil.SeqTrainParams |
Paramaters for training with a simple dataset |
| ClassifyCommandLineUtil.SeqTrainTestParams |
Specific TrainTestParameters for Sequential mode. |
| ClassifyCommandLineUtil.SimpleTestParams |
|
| ClassifyCommandLineUtil.SimpleTrainParams |
Paramaters for training with a simple dataset |
| ClassifyCommandLineUtil.SimpleTrainTestParams |
Specific TrainTestParameters for Simple/Standard mode. |
| ClassifyCommandLineUtil.TestParams |
Paramters for Test Classifier |
| ClassifyCommandLineUtil.TrainParams |
Parameters for training. |
| ClassifyCommandLineUtil.TrainTestParams |
Paramters for TrainTest Classifier. |
| ClassLabel |
A label which is associated with an instance---either by a classifier,
or in training data. |
| DatasetClassifierTeacher |
Trains a ClassifierLearner using the information in a labeled Dataset. |
| DatasetIndex |
An inverted index, mapping features to examples which contain the
features. |
| DatasetLoader |
Dataset i/o. |
| Example |
An instance that is associated with a ClassLabel. |
| ExampleSchema |
Defines legal formats for examples. |
| Explanation |
Provides a facitlity for constructing and displaying explanations for classification. |
| Explanation.Node |
A Node in the Explanation Tree |
| Feature |
A name for a feature. |
| FeatureFactory |
Creates Features, and maintains a mapping between Features and
numeric ids. |
| GUI |
Support routines for building GUI's to view datasets, instances, and
etc. |
| GUI.ExampleViewer |
A viewer for examples. |
| GUI.InstanceViewer |
A viewer for instances |
| ManyVsRestLearner |
Multi-class version of a binary classifier; Generalizes OneVsAllLearner. |
| MistakeCountingOnlineLearner |
A wrapper around on OnlineClassifierLearner that counts the number
of mistakes if makes. |
| MostFrequentFirstLearner |
Multi-class version of a binary classifier. |
| MutableInstance |
A single instance for a learner. |
| OneVsAllClassifier |
A Classifier composed of a bunch of binary classifiers, each of
which separates one class from the others. |
| OneVsAllLearner |
Multi-class version of a binary classifier. |
| OnlineBinaryClassifierLearner |
Abstract class which implements the 'getBinaryClassifier' method of BinaryClassifierLearner's. |
| OnlineClassifierLearner |
Abstract ClassifierLearner which instantiates the teacher-learner protocol
so as to implement a standard on-line learner. |
| OnlineVersion |
Online version of a BatchClassifierLearner. |
| RandomAccessDataset |
A dataset which supports random access to the examples. |
| SampleDatasets |
Some sample inputs for learners. |
| SGMExample |
An instance designed for a relational dataset. |
| SGMFeatureFactory |
For Stacked Graphical Learning. |
| StackedClassifierTeacher |
Implements the teacher's side of the learner-teacher protocol for SGM. |
| StackedDatasetClassifierTeacher |
Trains a StackedClassifierLearner using the information in a labeled relational Dataset. |
| StackedLearner |
Stacked generalization. |
| Test |
Main UI program for the 'classify' package. |
| Test.DataClassificationTask |
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| Train |
Main UI program for the 'classify' package. |
| Train.DataClassificationTask |
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| TrainTest |
Main UI program for the 'classify' package. |
| TrainTest.DataClassificationTask |
|
| TweakedLearner |
A Tweaked Learner, with an optimization of the precision vs. |
| TweakedLearner.TweakedClassifier |
A Tweaked Classifier, with an optimization of the precision vs. |
| UI |
Main UI program for the 'classify' package. |
| UI.DataClassificationTask |
|
| Util |
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| WeightedSet<T> |
Set of objects, each with an associated weight |