CFA Level I · CFA Level I Exam · Introduction to Financial Data Science
A data scientist has unlabeled data on customer transactions and wants to group customers into segments with similar spending behavior, without predefining the segments. Which technique is most appropriate?
Clustering is most appropriate. It is an unsupervised method that groups similar observations without predefined labels, which fits segmenting customers by spending behavior. Penalized regression and classification both require a labeled target variable, which this unlabeled dataset lacks.
- AClusteringCorrect
- BPenalized regression
- CClassification with a labeled target
Explanation
Clustering is an unsupervised technique that groups observations by similarity without labels. Penalized regression is a supervised method for prediction that reduces overfitting. Classification requires labeled categories, which are not available here.
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