Detail publikace

Combination of Logistic Regression and Boosting to Predict Disease Outcome

ŠILHAVÁ, J. SMRŽ, P.

Originální název

Combination of Logistic Regression and Boosting to Predict Disease Outcome

Typ

abstrakt

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

combining of heterogeneous data, gene expression data, class prediction, boosting

Autoři

ŠILHAVÁ, J.; SMRŽ, P.

Vydáno

8. 12. 2010

Místo

Ribno, Bled

ISBN

978-961-92487-4-4

Kniha

Applied Statistics 2010 International Conference

Strany od

35

Strany do

35

Strany počet

2

BibTex

@misc{BUT61068,
  author="Jana {Šilhavá} and Pavel {Smrž}",
  title="Combination of Logistic Regression and Boosting to Predict Disease Outcome",
  booktitle="Applied Statistics 2010 International Conference",
  year="2010",
  pages="35--35",
  address="Ribno, Bled",
  isbn="978-961-92487-4-4",
  note="abstract"
}