Random forest (RF) is a popular and powerful technique nowadays. It can be used for classification, regression and unsupervised clustering. In its original form introduced by Leo Breiman, RF is used as a predictive model to generate predictions for new observations. Recent researches have proposed several methods based on RF for feature selection and for generating prediction intervals. However, they are limited in their applicability and accuracy.
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- Partial requirement for: Ph.D., Arizona State University, 2017Note typethesis
- Includes bibliographical references (pages 102-107)Note typebibliography
- Field of study: Biomedical informatics