KNN Class Reference

Base class for item recommenders that use some kind of k-nearest neighbors (kNN) model. More...

Inheritance diagram for KNN:

List of all members.

Public Member Functions
virtual bool	CanPredict (int user_id, int item_id)
	Check whether a useful prediction (i.e. not using a fallback/default answer) can be made for a given user-item combination.
Object	Clone ()
	create a shallow copy of the object
override void	LoadModel (string filename)
	Get the model parameters from a file.
abstract float	Predict (int user_id, int item_id)
	Predict rating or score for a given user-item combination.
override void	SaveModel (string filename)
	Save the model parameters to a file.
override string	ToString ()
	Return a string representation of the recommender.
abstract void	Train ()
	Learn the model parameters of the recommender from the training data.
Protected Attributes
CorrelationMatrix	correlation
	Correlation matrix over some kind of entity.
uint	k = 80
	The number of neighbors to take into account for prediction.
int[][]	nearest_neighbors
	Precomputed nearest neighbors.
Properties
virtual IPosOnlyFeedback	Feedback [get, set]
	the feedback data to be used for training
uint	K [get, set]
	The number of neighbors to take into account for prediction.
int	MaxItemID [get, set]
	Maximum item ID.
int	MaxUserID [get, set]
	Maximum user ID.

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Detailed Description

Base class for item recommenders that use some kind of k-nearest neighbors (kNN) model.

See also:

MyMediaLite.ItemRecommendation.KNN

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Member Function Documentation

virtual bool CanPredict	(	int	user_id,
		int	item_id
	)		[inline, virtual, inherited]

Check whether a useful prediction (i.e. not using a fallback/default answer) can be made for a given user-item combination.

It is up to the recommender implementor to decide when a prediction is useful, and to document it accordingly.

Parameters:

user_id	the user ID
item_id	the item ID

Returns:

true if a useful prediction can be made, false otherwise

Implements IRecommender.

Object Clone

(

)

[inline, inherited]

create a shallow copy of the object

override void LoadModel

(

string

filename

)

[inline, virtual]

Get the model parameters from a file.

Parameters:

filename

the name of the file to read from

Implements ItemRecommender.

abstract float Predict	(	int	user_id,
		int	item_id
	)		[pure virtual, inherited]

Predict rating or score for a given user-item combination.

Parameters:

user_id	the user ID
item_id	the item ID

Returns:

the predicted score/rating for the given user-item combination

Implements IRecommender.

Implemented in BPRMF, BPRMF_ItemMapping, BPRLinear, BPRMF_UserMapping, ItemAttributeSVM, MF, MostPopularByAttributes, MostPopular, UserKNN, ItemKNN, WeightedItemKNN, Random, WeightedUserKNN, and Zero.

override void SaveModel

(

string

filename

)

[inline, virtual]

Save the model parameters to a file.

Parameters:

filename

the name of the file to write to

Implements ItemRecommender.

override string ToString

(

)

[inline, inherited]

Return a string representation of the recommender.

The ToString() method of recommenders should list the class name and all hyperparameters, separated by space characters.

Implements IRecommender.

Reimplemented in BPRMF, BPRMF_Mapping, BPRLinear, BPRMF_ItemMapping, BPRMF_UserMapping, WRMF, MultiCoreBPRMF, BPRMF_ItemMapping_Optimal, BPRMF_ItemMappingSVR, SoftMarginRankingMF, ItemAttributeSVM, BPRMF_UserMapping_Optimal, BPRMF_ItemMappingKNN, ItemKNN, UserKNN, WeightedBPRMF, ItemAttributeKNN, UserAttributeKNN, WeightedItemKNN, and WeightedUserKNN.

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Member Data Documentation

CorrelationMatrix correlation [protected]

Correlation matrix over some kind of entity.

uint k = 80 [protected]

The number of neighbors to take into account for prediction.

int [][] nearest_neighbors [protected]

Precomputed nearest neighbors.

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Property Documentation

virtual IPosOnlyFeedback Feedback [get, set, inherited]

the feedback data to be used for training

uint K [get, set]

The number of neighbors to take into account for prediction.

int MaxItemID [get, set, inherited]

Maximum item ID.

int MaxUserID [get, set, inherited]

Maximum user ID.

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The documentation for this class was generated from the following file:

• ItemRecommendation/KNN.cs