Linear model optimized for BPR
Declaring type: BPR_Linear
Namespace: MyMediaLite.ItemRecommendation
Assembly: MyMediaLite
Collapse/Expand Protected Fields
  Name Description
Protected Field iteration_length One iteration is iteration_length * number of entries in the training matrix
Collapse/Expand Public Constructors
  Name Description
Public Method BPR_Linear

There is no summary.

Collapse/Expand Public Methods (see also: Protected Methods)
  Name Description
Public Method ComputeFit

There is no summary.

Public Method Iterate Perform one iteration of stochastic gradient ascent over the training data. One iteration is iteration_length * number of entries in the training matrix
Public Method Virtual LoadModel

There is no summary.

Public Method Virtual Predict

There is no summary.

Public Method Virtual SaveModel

There is no summary.

Public Method Virtual ToString

There is no summary.

Public Method Virtual Train

There is no summary.

Collapse/Expand Protected Methods
  Name Description
Protected Method SampleItemPair Sample a pair of items, given a user
Protected Method SampleTriple Sample a triple for BPR learning
Protected Method SampleUser Sample a user that has viewed at least one and not all items
Protected Method Virtual UpdateFeatures Modified feature update method that exploits attribute sparsity
Collapse/Expand Public Properties
  Name Description
Public Property FastSamplingMemoryLimit Fast sampling memory limit, in MiB
Public Property InitMean mean of the Gaussian distribution used to initialize the features
Public Property InitStdev standard deviation of the normal distribution used to initialize the features
Public Property ItemAttributes

There is no summary.

Public Property LearnRate Learning rate alpha
Public Property NumItemAttributes

There is no summary.

Public Property NumIter Number of iterations over the training data
Public Property Regularization Regularization parameter