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Topic 3 Clustering data

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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: ClusteringIn 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 Node 1 Table Reader Exercise: ClusteringIn 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 Node 1 Table Reader

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Created by: kathrinmelcher
Created at: 2019-12-13
On NodePit since: 2024-08-17
Last update: 2024-11-21
Created with KNIME version: v5.2.0
Tags: clusterk-MeansalgorithmeducationGIDSacademiaexerciseTheGuideBook

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