Popular Ensemble Methods: An Empirical Study
نویسندگان
چکیده
منابع مشابه
Popular Ensemble Methods: An Empirical Study
An ensemble consists of a set of individually trained classifiers (such as neural networks or decision trees) whose predictions are combined when classifying novel instances. Previous research has shown that an ensemble is often more accurate than any of the single classifiers in the ensemble. Bagging (Breiman, 1996c) and Boosting (Freund & Schapire, 1996; Schapire, 1990) are two relatively new...
متن کاملEnsemble Monte-Carlo Planning: An Empirical Study
Monte-Carlo planning algorithms, such as UCT, select actions at each decision epoch by intelligently expanding a single search tree given the available time and then selecting the best root action. Recent work has provided evidence that it can be advantageous to instead construct an ensemble of search trees and to make a decision according to a weighted vote. However, these prior investigations...
متن کاملAn Empirical Comparison of Pruning Methods for Ensemble Classifiers
Many researchers have shown that ensemble methods such as Boosting and Bagging improve the accuracy of classification. Boosting and Bagging perform well with unstable learning algorithms such as neural networks or decision trees. Pruning decision tree classifiers is intended to make trees simpler and more comprehensible and avoid over-fitting. However it is known that pruning individual classif...
متن کاملAn empirical evaluation of ensemble adjustment methods for analogy-based effort estimation
Context: Effort adjustment is an essential part of analogy-based effort estimation, used to tune and adapt nearest analogies in order to produce more accurate estimations. Currently, there are plenty of adjustment methods proposed in literature, but there is no consensus on which method produces more accurate estimates and under which settings. Objective: This paper investigates the potential o...
متن کاملAn Empirical Validation Study of Popular Survey Methodologies for Sensitive Questions∗
When studying sensitive issues including corruption, prejudice, and sexual behavior, researchers have increasingly relied upon indirect questioning techniques to mitigate such known problems of direct survey questions as under-reporting and nonresponse. However, there have been surprisingly few empirical validation studies of these indirect techniques, because the information required to verify...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 1999
ISSN: 1076-9757
DOI: 10.1613/jair.614