k-nearest neighbor user-based collaborative filtering using cosine-similarity (unweighted) More...
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 | |
IList< int > | GetMostSimilarUsers (int user_id, uint n=10) |
get the most similar users | |
float | GetUserSimilarity (int user_id1, int user_id2) |
get the similarity between two users | |
override void | LoadModel (string filename) |
Get the model parameters from a file. | |
override 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. | |
override 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. |
k-nearest neighbor user-based collaborative filtering using cosine-similarity (unweighted)
k=inf equals most-popular.
This recommender does NOT support incremental updates.
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.
user_id | the user ID | |
item_id | the item ID |
Implements IRecommender.
Object Clone | ( | ) | [inline, inherited] |
create a shallow copy of the object
IList<int> GetMostSimilarUsers | ( | int | user_id, | |
uint | n = 10 | |||
) | [inline] |
get the most similar users
user_id | the ID of the user | |
n | the number of similar users to return |
Implements IUserSimilarityProvider.
float GetUserSimilarity | ( | int | user_id1, | |
int | user_id2 | |||
) | [inline] |
get the similarity between two users
user_id1 | the ID of the first user | |
user_id2 | the ID of the second user |
Implements IUserSimilarityProvider.
override void LoadModel | ( | string | filename | ) | [inline, virtual, inherited] |
Get the model parameters from a file.
filename | the name of the file to read from |
Implements ItemRecommender.
override float Predict | ( | int | user_id, | |
int | item_id | |||
) | [inline, virtual] |
Predict rating or score for a given user-item combination.
user_id | the user ID | |
item_id | the item ID |
Implements ItemRecommender.
Reimplemented in WeightedUserKNN.
override void SaveModel | ( | string | filename | ) | [inline, virtual, inherited] |
Save the model parameters to a file.
filename | the name of the file to write to |
Implements ItemRecommender.
override string ToString | ( | ) | [inline] |
Return a string representation of the recommender.
The ToString() method of recommenders should list the class name and all hyperparameters, separated by space characters.
Reimplemented from ItemRecommender.
Reimplemented in UserAttributeKNN, and WeightedUserKNN.
CorrelationMatrix correlation [protected, inherited] |
Correlation matrix over some kind of entity.
uint k = 80 [protected, inherited] |
The number of neighbors to take into account for prediction.
int [][] nearest_neighbors [protected, inherited] |
Precomputed nearest neighbors.
virtual IPosOnlyFeedback Feedback [get, set, inherited] |
the feedback data to be used for training
uint K [get, set, inherited] |
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.