In this example, Gaussian Mixture Model cluster analysis is performed on 3 variables giving the average credit, checking and savings balances of customers, yielding a requested 3 clusters.
Since Clustering in Teradata Warehouse Miner is non-deterministic, the results may vary from these, or from execution to execution.
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Parameterize a Cluster analysis as follows:
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Selected Tables and Columns
- twm_customer_analysis.avg_cc_bal
- twm_customer_analysis.avg_ck_bal
- twm_customer_analysis.avg_sv_bal
- Number of Clusters — 3
- Algorithm — Gaussian Mixture Model
- Convergence Criterion — 0.1
- Use Listwise deletion to eliminate null values — Enabled
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Selected Tables and Columns
- Run the analysis.
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Click Results when it completes.
For this example, the Clustering analysis generated the following pages. Since Clustering is non-deterministic, results may vary. A single click on each page name populates the page with the item.
Progress Iteration Log Likelihood Diff Timestamp 1 -25.63 0 3:05 PM 2 -25.17 .46 3:05 PM 3 -24.89 .27 3:05 PM 4 -24.67 .21 3:05 PM 5 -24.42 .24 3:05 PM 6 -24.33 .09 3:06 PM Solution Col Table_Name Column_Name Cluster_Id Weight Mean Variance 1 twm_customer_analysis avg_cc_bal 1 .175 -1935.576 3535133.504 2 twm_customer_analysis avg_ck_bal 1 .175 2196.395 9698027.496 3 twm_customer_analysis avg_sv_bal 1 .175 674.72 825983.51 1 twm_customer_analysis avg_cc_bal 2 .125 -746.095 770621.296 2 twm_customer_analysis avg_ck_bal 2 .125 948.943 1984536.299 3 twm_customer_analysis avg_sv_bal 2 .125 2793.892 11219857.457 1 twm_customer_analysis avg_cc_bal 3 .699 -323.418 175890.376 2 twm_customer_analysis avg_ck_bal 3 .699 570.259 661100.56 3 twm_customer_analysis avg_sv_bal 3 .699 187.507 63863.503