CFA Level I · CFA Level I Exam · Introduction to Financial Data Science
In a machine learning project, the data are divided into a training set, a validation set, and a test set. The test set is most likely used to:
The test set is used to estimate the final model's out-of-sample performance. It is held out until the end so it gives an unbiased assessment. Parameters are fit on the training set, and hyperparameters are tuned using the validation set.
- Atune the model's hyperparameters
- Bestimate the final model's out-of-sample performanceCorrect
- Cfit the model's parameters to the data
Explanation
The training set fits parameters and the validation set tunes hyperparameters and selects among models. The test set is held back until the end to give an unbiased estimate of out-of-sample performance.
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