k-Means Visualization

This component trains the data using k-Means clustering which is an unsupervised machine learning model and further performs dimension reduction to two features using PCA.
This component consists of one configuration node- Integer Configuration Node which is a hypoparameter and takes in the value of the number of clusters required. In this project, we use datasets with at least two columns and of type Double with values between 0 and 1.
For visualization, we see the color-coded data points on a Scatter Plot.

Options

Column Filter

Select atleast two columns of type Double

Number of clusters

Select the number of clusters (k).

Nodes

• k-Means2 ×
• Color Manager1 ×
• Column Filter Configuration1 ×
• Component Input1 ×
• Component Output1 ×
• Show all 8 nodes

Extensions

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

Links

• No links available