Review of Different Methods of Embedded Feature Selection in Machine Learning Models for Genetic Risk Prediction

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URL

Journal Title

Journal ISSN

Volume Title

Perustieteiden korkeakoulu | Bachelor's thesis
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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, Maarit

Thesis advisor

Wharrie, Sophie

Keywords

genetic risk scoring, machine learning, feature selection, lasso, random forest

Other note

Citation