Groundlearn / Glossary / Unsupervised learning
Unsupervised learning
A CFA term, defined in plain English with the distinction examiners test.
What it means
Machine learning that finds structure in data without a target variable, for example by grouping similar observations into clusters.
The exam angle
If the question has no labelled outcome to predict, the answer is unsupervised.
Where it appears in the syllabus
- Quantitative MethodsCFA Level I · exam weight 11–14% · Returns and benchmarks, time value, distributions, portfolio maths, regression.
- Quantitative MethodsCFA Level II · exam weight 5–10% · Multiple regression, misspecification, time series, machine learning.
Related terms
- Coefficient of determinationThe fraction of the dependent variable’s variation explained by the regression.
- Linear regressionFitting a straight line through data by minimising the sum of squared residuals, to explain a dependent variable by…
- OverfittingA model that fits the noise in its training data as well as the signal, so it performs well in-sample and poorly on…
- Supervised learningMachine learning that fits a model to examples with known outcomes — labelled data — so it can predict the outcome for…
- AlphaReturn in excess of what the asset’s risk exposures would predict.
- AnnuityA series of equal cash flows at equal intervals.
Educational content only. This is not financial, investment, legal or regulatory advice. Check the official curriculum for your own exam before relying on any definition here.
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