Conclusions with Confusion – or Decision Trees
Following up from Learning about Clustering Analysis with Predictive Analysis it looks like cluster 3 is the most valuable. To validate, I look at Decision Trees in Predictive Analysis 1.14:
I set it up as trend, classification and the 4 key measures of rental price, count, revenue and margin. I also read up about decision trees in Wikipedia
The target variable is the cluster number from the R K means analysis. After running the analysis one of the visualizations available is the confusion matrix:
Of course to learn more about this I turn to Wikipedia to learn more about Confusion Matrix
The decision tree above shows that cluster 2 may be more valuable than cluster 3, so maybe I should target those customers.