Simple matrix factorization class
Declaring type: MatrixFactorization
Namespace: MyMediaLite.RatingPredictor
Assembly: MyMediaLite
Collapse/Expand Protected Fields
  Name Description
Protected Field global_bias The bias (global average)
Protected Field item_factors Matrix containing the latent item factors
Protected Field learn_rate Learn rate
Protected Field num_factors Number of latent factors
Protected Field regularization Regularization parameter
Protected Field user_factors Matrix containing the latent user factors
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Collapse/Expand Public Constructors
  Name Description
Public Method MatrixFactorization

There is no summary.
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Collapse/Expand Public Methods (see also: Protected Methods)
  Name Description
Public Method Virtual AddItem

There is no summary.
Public Method Virtual AddRating

There is no summary.
Public Method Virtual AddUser

There is no summary.
Public Method ComputeFit Compute approximated fit (RMSE) on the training data
Public Method Virtual Iterate

There is no summary.
Public Method Virtual LoadModel

There is no summary.
Public Method Virtual Predict Predict the rating of a given user for a given item.
Public Method Virtual RemoveItem

There is no summary.
Public Method Virtual RemoveRating

There is no summary.
Public Method Virtual RemoveUser

There is no summary.
Public Method RetrainItem Updates the latent factors of an item
Public Method RetrainUser Updates the latent factors on a user
Public Method Virtual SaveModel

There is no summary.
Public Method Virtual ToString

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Public Method Virtual Train

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Public Method Virtual UpdateRating

There is no summary.
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Collapse/Expand Protected Methods
  Name Description
Protected Method Virtual Iterate Iterate once over rating data and adjust corresponding factors (stochastic gradient descent).
Protected Method Predict

There is no summary.
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Collapse/Expand Public Properties
  Name Description
Public Property InitMean Mean of the normal distribution used to initialize the factors
Public Property InitStdev Standard deviation of the normal distribution used to initialize the factors
Public Property LearnRate Learn rate
Public Property NumFactors Number of latent factors
Public Property NumIter Number of iterations over the training data
Public Property Regularization Regularization parameter
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