Statements (49)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:algorithm
|
| gptkbp:advantage |
simple to implement
no training phase sensitive to irrelevant features sensitive to the scale of data computationally expensive at prediction time |
| gptkbp:alternativeName |
k nearest neighbor
k-nearest neighbour kNN kNN classifier |
| gptkbp:application |
bioinformatics
image recognition recommender systems anomaly detection text categorization |
| gptkbp:canBe |
binary classification
multiclass classification multi-label classification |
| gptkbp:category |
instance-based learning
lazy learning |
| gptkbp:commonLibrary |
gptkb:Weka
gptkb:scikit-learn gptkb:MLlib |
| gptkbp:field |
gptkb:machine_learning
pattern recognition |
| gptkbp:fullName |
k-nearest neighbors
|
| gptkbp:hasConcept |
classifies a sample based on the majority label among its k nearest neighbors
|
| https://www.w3.org/2000/01/rdf-schema#label |
k-NN
|
| gptkbp:hyperparameter |
k (number of neighbors)
|
| gptkbp:introduced |
gptkb:Evelyn_Fix
Joseph Hodges |
| gptkbp:introducedIn |
1951
|
| gptkbp:measures |
gptkb:Hamming_distance
gptkb:Manhattan_distance gptkb:Minkowski_distance Euclidean distance |
| gptkbp:output |
class label
regression value |
| gptkbp:requires |
feature scaling
|
| gptkbp:supportsAlgorithm |
nearest centroid classifier
radius neighbors classifier weighted k-NN |
| gptkbp:type |
supervised learning
non-parametric method |
| gptkbp:usedFor |
gptkb:dictionary
regression |
| gptkbp:bfsParent |
gptkb:OpenSearch_Plugins
gptkb:KNN_(K-Nearest_Neighbors) |
| gptkbp:bfsLayer |
8
|