## Uses of Interface
org.apache.mahout.classifier.sgd.PriorFunction

Packages that use PriorFunction
org.apache.mahout.classifier.sgd: Implements a variety of on-line logistric regression classifiers using SGD-based algorithms.

Uses of PriorFunction in org.apache.mahout.classifier.sgd

Classes in org.apache.mahout.classifier.sgd that implement PriorFunction
`class` `ElasticBandPrior` Implements a linear combination of L1 and L2 priors.
`class` `L1` Implements the Laplacian or bi-exponential prior.
`class` `L2` Implements the Gaussian prior.
`class` `TPrior` Provides a t-distribution as a prior.
`class` `UniformPrior` A uniform prior.

Fields in org.apache.mahout.classifier.sgd declared as PriorFunction
`protected PriorFunction` `AbstractOnlineLogisticRegression.prior`

Methods in org.apache.mahout.classifier.sgd that return PriorFunction
`PriorFunction` `CrossFoldLearner.getPrior()`
`PriorFunction` `AdaptiveLogisticRegression.getPrior()`
`PriorFunction` `AbstractOnlineLogisticRegression.getPrior()`

Methods in org.apache.mahout.classifier.sgd with parameters of type PriorFunction
`void` `CrossFoldLearner.setPrior(PriorFunction prior)`
`void` `AbstractOnlineLogisticRegression.setPrior(PriorFunction prior)`

Constructors in org.apache.mahout.classifier.sgd with parameters of type PriorFunction
`AdaptiveLogisticRegression.Wrapper(int numCategories, int numFeatures, PriorFunction prior)`
`AdaptiveLogisticRegression(int numCategories, int numFeatures, PriorFunction prior)` Uses `AdaptiveLogisticRegression.DEFAULT_THREAD_COUNT` and `AdaptiveLogisticRegression.DEFAULT_POOL_SIZE`
`AdaptiveLogisticRegression(int numCategories, int numFeatures, PriorFunction prior, int threadCount, int poolSize)`
`CrossFoldLearner(int folds, int numCategories, int numFeatures, PriorFunction prior)`
`OnlineLogisticRegression(int numCategories, int numFeatures, PriorFunction prior)`

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