Package | Description |
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org.apache.mahout.classifier.sgd |
Implements a variety of on-line logistric regression classifiers using SGD-based algorithms.
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Class and Description |
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AbstractOnlineLogisticRegression
Generic definition of a 1 of n logistic regression classifier that returns probabilities in
response to a feature vector.
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AdaptiveLogisticRegression
This is a meta-learner that maintains a pool of ordinary
OnlineLogisticRegression learners. |
AdaptiveLogisticRegression.TrainingExample |
AdaptiveLogisticRegression.Wrapper
Provides a shim between the EP optimization stuff and the CrossFoldLearner.
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CrossFoldLearner
Does cross-fold validation of log-likelihood and AUC on several online logistic regression
models.
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CsvRecordFactory
Converts CSV data lines to vectors.
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Gradient
Provides the ability to inject a gradient into the SGD logistic regresion.
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GradientMachine
Online gradient machine learner that tries to minimize the label ranking hinge loss.
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ModelDissector.Weight |
OnlineLogisticRegression
Extends the basic on-line logistic regression learner with a specific set of learning
rate annealing schedules.
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PassiveAggressive
Online passive aggressive learner that tries to minimize the label ranking hinge loss.
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PriorFunction
A prior is used to regularize the learning algorithm.
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RecordFactory
A record factor understands how to convert a line of data into fields and then into a vector.
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