Figure 4 Cluster Density b In the Cluster Representations pane select Feature

Figure 4 cluster density b in the cluster

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Figure 4: Cluster Density b. In the Cluster Representations pane, select Feature Distribution.
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MIS688: Predictive Analytics 6 i. The graph lets you compare the distribution of the variable in a particular cluster against the entire dataset. You can change the Measure being displayed and the cluster number in the Data panel on the right side. Figure 5: Feature Distribution c. In the Cluster Representations pane, select Cluster Center Representation. i. You see a radar chart of the cluster centers (radar axes are the variables); you can change the cluster number in the Data panel Figure 6: Radar Chart of Clusters c. In the Cluster Representations pane, select Parallel Coordinate Chart. i. The axes are all normalized. Parallel lines between the axes imply a positive relationship between the two dimensions. Intersecting lines imply a negative relationship.
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MIS688: Predictive Analytics 7 Figure 7: Parallel Coordinates Chart d. In the Cluster Representations pane, select Scatter Matrix Charts. i. You see the scatter charts of store clusters plotted between various pairs of dimensions Figure 8: Scatter Plots 27. The fitted and forecast results are stored in the CSV file. You can open the saved csv file and explore the three clusters that have been generated. 28. From the File menu, select Save . 29. Enter a name for the document. 30. Choose Save
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