I want to cluster users based on their acceptance of chatbots. I'm considering 5 dimensions of acceptance and each of them has 3-4 questions. So in total, I have around 20 questions which represent 5 variables. What is the best way to choose the most significant representative question for each variable?
Xiaolin Xing
Before cluster analysis, reducing variables is crucial. Correlation Analysis can eliminate redundant variables, while Principal Component Analysis (PCA) captures significant data variance in fewer components. Using Domain Knowledge or determining Feature Importance with Tree-based Models can also guide variable selection. Post-reduction validation ensures meaningful clustering remains.
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