Use the selected KNN classifier and the feature weights, FeatureWeights, to classify the chosen Pattern. A TableOfReal object containing verbose information on the decision process will be created.

Settings

k neighbours

The size of the neighbourhood.

Vote weighting

The type of vote weighting to be used.

Output

Specifies the degree of verbosity, where winners only generates a TableOfReal containing information on the instances of the winning category only whereas All candidates results in a TableOfReal with verbose information on all unique categories in the neighbourhood defined by the parameter k.

See also:

kNN classifiers 1.1.1. Feature weighting

kNN classifiers 1.1.1.1. Filter-based feature weighting

kNN classifiers 1.1.1.2. Wrapper-based feature weighting

kNN classifiers 1.1. Improving classification accuracy

kNN classifiers 1. What is a kNN classifier?

kNN classifiers

Links to this page

• kNN classifiers 3. Command overview