Clustering in Tableau for Beginers .pptx

Clustering in Tableau

1. Clustering in Tableau

2. A method of combining data into similar groups based on provided variables *Tableau uses color to distinguish between clusters Clustering Analysis

3. When Would I Use Clustering?

4. Recommendations Location Planning Customer Loyalty Programs Climate Change Use Cases

5. Step 4: Analyze the Clusters

6. How Does Clustering Work?

7. Tableau uses the k-means algorithm for clustering. For a given number of clusters k, the algorithm partitions the data into k clusters. Each cluster has a center (centroid) that is the mean value of all the points in that cluster. Clustering

8. Testing Accuracy

9.     x Calinski-Harabasz criterion

10. Variables: Sum of CO2 emissions per capita (metric tons) Sum of CO2 emissions, total (KtCO2) Level of Detail: Country name Scaling: Normalized Inputs for Clustering

11. Number of Clusters: 5 Number of Points: 218 Between-group Sum of Squares: 5.0161 Within-group Sum of Squares: 0.64986 Total Sum of Squares: 5.6659 Summary Diagnostics