منابع مشابه
Extending Statistical Boosting
A. Mayr1; H. Binder2; O. Gefeller1; M. Schmid1,3 1Institut für Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany; 2Institut für Medizinische Biometrie, Epidemiologie und Informatik, Johannes Gutenberg-Universität Mainz, Germany; 3Institut für Medizinische Biometrie, Informatik und Epidemiologie, Rheinische Friedrich-Wilhelms-Universität B...
متن کاملDiscussion of "the evolution of boosting algorithms" and "extending statistical boosting".
This article is part of a For-Discussion-Section of Methods of Information in Medicine about the papers "The Evolution of Boosting Algorithms - From Machine Learning to Statistical Modelling" and "Extending Statistical Boosting - An Overview of Recent Methodological Developments", written by Andreas Mayr and co-authors. It is introduced by an editorial. This article contains the combined commen...
متن کاملBoosting Statistical Word Alignment
This paper proposes an approach to improve statistical word alignment with the boosting method. Applying boosting to word alignment must solve two problems. The first is how to build the reference set for the training data. We propose an approach to automatically build a pseudo reference set, which can avoid manual annotation of the training set. The second is how to calculate the error rate of...
متن کاملBagging and Boosting statistical machine translation systems
a r t i c l e i n f o a b s t r a c t In this article we address the issue of generating diversified translation systems from a single Statistical Machine Translation (SMT) engine for system combination. Unlike traditional approaches, we do not resort to multiple structurally different SMT systems, but instead directly learn a strong SMT system from a single translation engine in a principled w...
متن کاملBoosting statistical application identification by flow correlation
In this paper, we propose a new online method for traffic classification that combines the statistical and host-based approaches in order to construct a robust and precise method for early Internet traffic identification. We use the packet size as the main feature for the classification and we benefit from the traffic profile of the host (i.e., which application and how much) to decide in favor...
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: Methods of Information in Medicine
سال: 2014
ISSN: 0026-1270,2511-705X
DOI: 10.3414/me13-01-0123