K Means VAL

The function performs fast K-Means clustering algorithm and returns cluster means and averages. Specifically, the rows associated with positive cluster IDs in output contain the average values of each of the clustered columns and the count for each cluster ID. The rows associated with negative cluster IDs contain the variance of each of the clustered columns for each cluster ID. There is an additional optional input table that specifies the dataset containing clustering output.

Options

Centers

Specifies the number of clusters to be contained in the cluster model.

Input Columns

Specifies the name(s) of the column(s) to be used in clustering.

Maximum Iterations

Specifies the maximum number of iterations to perform during clustering.

Threshold

Specifies the value which determines if the algorithm has converged based on how much the cluster centroids change from one iteration to the next.

Output Schema

Output Schema, if Volatile is true then use user login as the schema.

Output Table

Output Table

VAL Location

VAL Location

Nodes

• String Configuration3 ×
• Integer Configuration2 ×
• Python Script2 ×
• Column Filter Configuration1 ×
• Component Input1 ×
• Show all 14 nodes

Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Database
• FeatureKNIME Quick Forms

Links

• No links available