Non-Parametric Regression

k-Nearest Neighbors

$k$-Nearest Neighbors is a clustering-based algorithm for classification and regression. It is a a type of instance-based learning as it does not attempt to construct a general internal model, but simply stores instances of the training data. Prediction is computed from a simple majority vote of the nearest neighbors of each point: a query point is assigned the data class which has the most representatives within the nearest neighbors of the point.

Source of Description and Image: scikit-learn

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Clustering 27 6.59%
Retrieval 24 5.85%
General Classification 20 4.88%
Classification 17 4.15%
Self-Supervised Learning 11 2.68%
regression 9 2.20%
Image Retrieval 9 2.20%
Dimensionality Reduction 9 2.20%
graph partitioning 9 2.20%

Components


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

Categories