AdaBoost has been theoretically and empirically proved to be a very successful ensemble learning algorithm, which iteratively generates a set of diverse weak learners and combines their outputs using the weighted majority voting rule as the final decision. However, in some cases, AdaBoost leads to overfitting especially for mislabeled noisy training examples, resulting in both its degraded gene...

Discuss approaches to combine techniques used by ensemble learning methods. Randomness which is used by Bagging and Random Forests is introduced into Adaboost to get robust performance under noisy situation. Declare that when the randomness introduced into AdaBoost equals to 100, the proposed algorithm turns out to be a Random Forests with weight update technique. Approaches are discussed to im...

In this letter, we present useful features accounting for pronunciation prominence and propose a classification technique for prominence detection. A set of phone-specific features are extracted based on a forced alignment of the test pronunciation provided by a speech recognition system. These features are then applied to the traditional classifiers such as the support vector machine (SVM), ar...

Article history: Received 15 September 2010 Available online 22 November 2011 Communicated by F. Roli

In this study, the authors propose the spatial codification of label predictions within the multi-scale stacked sequential learning (MSSL) framework, a successful learning scheme to deal with non-independent identically distributed data entries. After providing a motivation for this objective, they describe its theoretical framework based on the introduction of the blurred shape model as a smar...

Abstract: This paper investigates the detection and classification of fighting and pre and post fighting events when viewed from a video camera. Specifically we investigate normal, pre, post and actual fighting sequences and classify them. A hierarchical AdaBoost classifier is described and results using this approach are presented. We show it is possible to classify pre-fighting situations usi...

هدف: به‌کارگیری فناوری رایانش ابری، روند جدیدی در جهان امروز می‌باشد. ابری یکی از فناوری‌های اطلاعاتی نسل جدید است که روز به بیشتر کشورها محبوبیت بیشتری پیدا می‌کند. سال‌های اخیر سازمان‌ها شروع انتخاب مدل‌های خود می‌کنند. مؤسسات آموزشی، به‌ویژه دانشگاه‌ها و مدارس، نمی‌توانند مزایای قابل توجهی را برای آن‌ها همراه دارد، نادیده بگیرند با توجه رو رشد استفاده آن غفلت نمایند. هدف اصلی این پژوهش شناسا...

Robust face detection in complex airport environment is a challenging task. The complexity in such detection systems stems from the variances in image background, view, illumination, articulation, and facial expression. This paper presents the S-AdaBoost, a new variant of AdaBoost developed for the face detection system for airport operators (FDAO). In face detection application, the contributi...

Based on the analysis and distribution of network attacks in KDDCup99 dataset and real time traffic, this paper proposes a design of multi stage filter which is an efficient and effective approach in dealing with various categories of attacks in networks. The first stage of the filter is designed using Enhanced Adaboost with Decision tree algorithm to detect the frequent attacks occurs in the n...

Recent work has shown that combining multiple versions of weak classiiers such as decision trees or neural networks results in reduced test set error. To study this in greater detail, we analyze the asymptotic behavior of AdaBoost. The theoretical analysis establishes the relation between the distribution of margins of the training examples and the generated voting classiication rule. The paper...