K Nearest Neighbor (Distance Function)

Classifies a set of test data based on the k Nearest Neighbor algorithm using the training data.

Note that for the Euclidean distance on numeric columns the other K Nearest Neighbor node performs better as it uses an efficient index structure. The implementation of this node performs an exhaustive search of all points to all potential neighbors and is therefore suited for small to medium data sets only.

Options

Column with class labels: Select column to be used as classification attribute.
Number of neighbours to consider (k): Select the number of nearest neighbors used to classify a new instance. An odd number is recommended to avoid ties.
Weight neighbours by distance: Includes the distance of the query pattern to the stored training patterns into the classification. Closer neighbors have greater influence on the resulting class than the ones further away. (Still only k neighbors will be considered, however!)
Output class probabilities: If this option in enabled, additional columns, containing the class probabilities, will be appended to the output table.

Input Ports

: Input port for the training data
: Input port for the test data
: The distance function to use.

Output Ports

: Output data with class labels

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Installation

To use this node in KNIME, install the extension KNIME Distance Matrix from the below update site following our NodePit Product and Node Installation Guide:

v5.4

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.4.0.v202408081025

On NodePit since: 2024-12-06

Last update: 2024-12-17

KNIME versions: Since v3.7

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