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Basic Question 3 of 8
A hyperparameter is a parameter whose value ______ by the researcher.
B. can be adjusted as the learning progresses.
C. should be set after the learning and before applying to validation and test data.
A. must be set before learning begins.
B. can be adjusted as the learning progresses.
C. should be set after the learning and before applying to validation and test data.
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Learning Outcome Statements
describe supervised machine learning algorithms - including penalized regression, support vector machine, k-nearest neighbor, classification and regression tree, ensemble learning, and random forest - and determine the problems for which they are best suited;
CFA® 2025 Level II Curriculum, Volume 1, Module 6.