Classification and regression tree (CART) methods are a class of data mining techniques which constitute an alternative approach to classical regression. CART methods are frequently used in ...
Canadian Journal of Public Health / Revue Canadienne de Santé Publique, Vol. 100, No. 4 (July/August 2009), pp. 263-267 (5 pages) Objectives: A prospective, observational study was undertaken to ...
Objective: To determine whether classification tree techniques used on survey data collected at enrollment from older adults in a Medicare HMO could predict the likelihood of an individual being in a ...
Morbidity After Sentinel Lymph Node Biopsy in Primary Breast Cancer: Results From a Randomized Controlled Trial Data were uniformly collected on 1,433 referred men with a serum prostate-specific ...
Objective: The aim of this study was to establish a statistical model for prediction neonatal deaths. Methods: A case-control study was carried out in the State of Maranhao, Northeast Brazil. The ...
Dr. James McCaffrey of Microsoft Research says the technique is easy to tune, works well with small datasets and produces highly interpretable predictions, but there are also trade-off cons. The goal ...
This article proposes a novel paradigm for building regression trees and ensemble learning in survival analysis. Generalizations of the classification and regression trees (CART) and random forests ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the AdaBoost.R2 algorithm for regression problems (where the goal is to predict a single numeric value). The ...
Morbidity After Sentinel Lymph Node Biopsy in Primary Breast Cancer: Results From a Randomized Controlled Trial Data were uniformly collected on 1,433 referred men with a serum prostate-specific ...
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