Ensemble Methods of Computational Inference
Prognostic modeling of tumor classes, disease status, and survival time based on information obtained from gene expression profiling techniques is studied in this chapter. The basic principles of ensemble methods like bagging, random forests, and boosting are explained. The application of those methods to data from patients suffering acute lymphoblastic leukemia or renal cell cancer is illustrated. The problem of identifying the best method for a certain prediction task is addressed by means of benchmark experiments.
KeywordsAcute Lymphoblastic Leukemia Random Forest Bootstrap Sample Renal Cell Cancer Ensemble Method
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