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TO FIND THE K NEAREST NEIGHBOUR ::
FORMULA ::
Class = knnclassify(Test, Training, Group, k, distance, rule)
INPUTS :-
TEST SET, TRAINING SET, GROUP, VALUE OF K, DISTANCE, RULE
TEST, TRAINING - MATRIX
GROUP - GROUPING OF ROWS
K - NUMBER OF NEAREST NEIGHBOR USED IN CLASSIFICATION
DISTANCE - EUCLIDEAN
RULE - NEAREST
OUTPUT :-
CLASS MATRIX WHICH SHOWS THE NEAREST NEIGHBORS OF EACH ROW ie.,ROW 1 OF TEST IS CLOSEST TO ROW 3 OF TRAINING.THEN I CALCULATED TRUE POSITIVE, TRUE NEGATIVE, FALSE POSITIVE, FALSE NEGATIVE USING THAT I CALCULATED ACCURACY, PRESICION, RECALL
Cite As
Aravind Manimaran (2026). 1-nearest neighbor with accuracy, precision and recall (https://www.mathworks.com/matlabcentral/fileexchange/31612-1-nearest-neighbor-with-accuracy-precision-and-recall), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.0.0 (2.4 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 |
