2-D Projection of Clustered Data

This component perfoms k-means clustering on the input data and then reduce the clustered data to 2 dimensions using PCA. Additionally, the 2D data are color endcoded based on the cluster they are contained in. Finally they are visualized using a scatter plot.

The number of clusters for K-Means and the maximum number of iterations can be set via the component dialog box. The default values for K and maximum iterations are 2 and 99 respectively .

This component works with any input data with at least 2 columns of type double with values between the range of 0 and 1.

Options

Max. Number of Iterations

Maximum number of iterations for K-Means

Number of Clusters (K)

Number of clusters expected

Nodes

• Integer Configuration2 ×
• Color Manager1 ×
• Component Input1 ×
• Component Output1 ×
• Merge Variables1 ×
• Show all 8 nodes

Extensions

• FeatureKNIME Base nodes
• FeatureKNIME JavaScript Views
• FeatureKNIME Quick Forms

Links

• No links available