Review of Different Methods of Embedded Feature Selection in Machine Learning Models for Genetic Risk Prediction
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Journal Title
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Perustieteiden korkeakoulu |
Bachelor's thesis
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Authors
Date
2023-04-28
Department
Major/Subject
Data Science
Mcode
SCI3095
Degree programme
Aalto Bachelor’s Programme in Science and Technology
Language
en
Pages
30+6
Series
Description
Supervisor
Korpi-Lagg, MaaritThesis advisor
Wharrie, SophieKeywords
genetic risk scoring, machine learning, feature selection, lasso, random forest