Icon

Clustering_​Assignment4

Clustering

- Filter rows
- Train a k-Means model
- Visualize clustered entries on Scatter plot and OSM Map
- Calculate Silhouette Coefficients

URL: Guide to Intelligent Data Science https://www.datascienceguide.org/

Exercise: Clustering In this exercise we will use the k-Means algorithm to cluster location data. 1) Read the dataset location_data.table2) Filter to entries from California (region_code = CA)3) Train a k-means model with k=3. Use only position data for clustering (latitude and longitude)4) Calculate the Silhoutte Coefficients using the Silhouette Coefficient node5) Plot latitude and longitude in a view (OSM Map or Scatter Plot) and use that to help you visually optimize k
Table Reader
Row Filter
Column Filter
k-Means
Distance Matrix Calculate
Scatter Plot
Silhouette Coefficient
Color Manager
OSM Map View

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: kathrinmelcher
Created at: 2019-12-13
On NodePit since: 2025-10-22
Last update: 2025-10-22
Created with KNIME version: v5.8.0
Tags: clusterk-MeansalgorithmeducationGIDSacademiaexerciseTheGuideBook

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!