Publication Details

Combination of Logistic Regression and Boosting to Predict Disease Outcome

ŠILHAVÁ Jana and SMRŽ Pavel. Combination of Logistic Regression and Boosting to Predict Disease Outcome. Applied Statistics 2010 International Conference. Ribno, Bled, 2010. ISBN 978-961-92487-4-4.
Czech title
Combination of Logistic Regression and Boosting to Predict Disease Outcome
Type
abstract
Language
english
Authors
Keywords
combining of heterogeneous data, gene expression data, class prediction, boosting
Annotation
An important current bioinformatic challenge is incorporation of diverse data types. Different bioinformatic data can provide complementary information. The combination of relevant data may lead to more accurate findings, e.g., it can help to understand complex diseases or it can derive more accurate hybrid diagnostic or prognostic signature. We propose a prediction approach that combines logistic regression and boosting. Logistic regression is employed with low-dimensional data, while boosting uses high-dimensional data. The presented approach is extended and incorporates more than two data sources. It is validated using simulated data sets and then applied to real bioinformatic data sets with clinical variables, gene expression data and SNP data. We show that this kind of data combination can increase predictive performance.

Published
2010
Pages
35-35
Book
Applied Statistics 2010 International Conference
Conference
Applied Statistics 2010, Ribno (Bled), Slovenia, SI
ISBN
978-961-92487-4-4
Place
Ribno, Bled, SI
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