This is the complete list of members for
ItemKNN, including all inherited members.
AddFeedback(ICollection< Tuple< int, int >> feedback) | ItemKNN | [inline, virtual] |
AddItem(int item_id) (defined in ItemKNN) | ItemKNN | [inline, protected, virtual] |
AddUser(int user_id) (defined in IncrementalItemRecommender) | IncrementalItemRecommender | [inline, protected, virtual] |
Alpha | KNN | |
CanPredict(int user_id, int item_id) | Recommender | [inline, virtual] |
Clone() | Recommender | [inline] |
Correlation | KNN | |
correlation_matrix | KNN | [protected] |
DataMatrix | ItemKNN | [protected] |
Feedback | ItemRecommender | |
GetItemSimilarity(int item_id1, int item_id2) | ItemKNN | [inline] |
GetMostSimilarItems(int item_id, uint n=10) | ItemKNN | [inline] |
K | KNN | |
k | KNN | [protected] |
KNN() | KNN | [inline] |
LoadModel(string filename) | KNN | [inline, virtual] |
MaxItemID | Recommender | |
MaxUserID | Recommender | |
nearest_neighbors | KNN | [protected] |
Predict(int user_id, int item_id) | ItemKNN | [inline, virtual] |
Q | KNN | |
Recommend(int user_id, int n=-1, System.Collections.Generic.ICollection< int > ignore_items=null, System.Collections.Generic.ICollection< int > candidate_items=null) (defined in Recommender) | Recommender | [inline, virtual] |
MyMediaLite::IRecommender.Recommend(int user_id, int n=-1, ICollection< int > ignore_items=null, ICollection< int > candidate_items=null) | IRecommender | |
RemoveFeedback(ICollection< Tuple< int, int >> feedback) | ItemKNN | [inline, virtual] |
RemoveItem(int item_id) | IncrementalItemRecommender | [inline, virtual] |
RemoveUser(int user_id) | IncrementalItemRecommender | [inline, virtual] |
ResizeNearestNeighbors(int new_size) | KNN | [inline, protected] |
SaveModel(string filename) | KNN | [inline, virtual] |
ToString() | KNN | [inline] |
Train() | ItemKNN | [inline, virtual] |
Update(ICollection< Tuple< int, int >> feedback) | KNN | [inline, protected] |
UpdateItems | IncrementalItemRecommender | |
UpdateUsers | IncrementalItemRecommender | |
Weighted | KNN | |