K Nearest Neighbor (Distance Function)

This Node Is Deprecated — This version of the node has been replaced with a new and improved version. The old version is kept for backwards-compatibility, but for all new workflows we suggest to use the version linked below.
Go to Suggested ReplacementK 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.


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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