CFA Level I · CFA Level I Exam · Introduction to Financial Data Science
An analyst wants to group thousands of retail borrowers into segments based on spending behavior, without any predefined labels for the groups. Which approach is most appropriate?
Unsupervised learning is most appropriate. The analyst has no predefined labels or target variable and wants the algorithm to discover natural groupings in borrower behavior, which is clustering. Supervised learning requires labeled outcomes, so it does not suit this segmentation problem.
- AUnsupervised learningCorrect
- BSupervised learning
- CReinforcement learning with labeled outcomes
Explanation
Grouping observations without predefined labels is a clustering task, which is unsupervised learning. Supervised learning needs labeled target outcomes, which are absent here. Reinforcement learning relies on reward feedback from actions, which does not fit segmentation of existing data.
Did you get it right without looking?
One question tells you little. A timed set on Introduction to Financial Data Science shows your real accuracy, how long you take and where you lose marks.
More Introduction to Financial Data Science questions
- A fund uses a model that classifies firms as likely to default or not, using labeled historical data on past defaults and firm characteristi…
- A data scientist builds a model that fits the training data almost perfectly but produces poor predictions on new data. The problem is most …
- A data scientist builds a model with many features and finds it fits the training set almost perfectly but performs poorly out of sample. Wh…
- An analyst has the following values for a feature: 8, 10, 12, 14, 56. The analyst applies min-max normalization to the value 14. The normali…
- An analyst trains a model to predict whether a borrower will default, using historical loans that are each labeled "default" or "no default.…
- An analyst converts a set of earnings call transcripts into a form suitable for modeling. She removes punctuation, converts all letters to l…