نتایج جستجو برای: adaboost classifier

تعداد نتایج: 45412  

Journal: :Pattern Recognition 2007
Yanmin Sun

The classification of data with imbalanced class distributions has posed a significant drawback in the performance attainable by most well-developed classification systems, which assume relatively balanced class distributions. This problem is especially crucial in many application domains, such as medical diagnosis, fraud detection, network intrusion, etc., which are of great importance in mach...

2016
Jianfang Cao Lichao Chen Min Wang Hao Shi Yun Tian

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural...

2009
Tarek Abudawood Peter A. Flach

Subgroup discovery aims at finding subsets of a population whose class distribution is significantly different from the overall distribution. It has previously predominantly been investigated in a two-class context. This paper investigates multi-class subgroup discovery methods. We consider six evaluation measures for multi-class subgroups, four of them new, and study their theoretical properti...

2007
Matías Arenas Javier Ruiz-del-Solar Rodrigo Verschae

In the present article a framework for the robust detection of mobile robots using nested cascades of boosted classifiers is proposed. The boosted classifiers are trained using Adaboost and domain-partitioning weak hypothesis. The most interesting aspect of this framework is its capability of building robot detection systems with high accuracy in dynamical environments (RoboCup scenario), which...

2005
Benjamin Laxton

This work presents a parts-based person detection framework. The individual body segmentslegs, torsos, and heads are detected by Adaboost classifiers, which have proven useful other classification tasks [12] [6] [1] [13]. The body segment candidates are combined into kinematically plausible configurations and each is assigned a score. The body configurations are calculated using an efficient dy...

Journal: :Computational Intelligence 2003
Kai Ming Ting Zijian Zheng

This article investigates boosting naive Bayesian classification. It first shows that boosting does not improve the accuracy of the naive Bayesian classifier as much as we expected in a set of natural domains. By analyzing the reason for boosting’s weakness, we propose to introduce tree structures into naive Bayesian classification to improve the performance of boosting when working with naive ...

Journal: :Jurnal Sistem Informasi 2023

Classification in supervised learning is a way to find patterns data base that the classes are already known. In classification of machine learning, there term called ensemble classifier. The workings classifier aimed improve model accuracy and optimize performance. This study aims analyze comparison algorithms work with , including Random Forest, Support Vector Machine (SVM), AdaBoost. used Hu...

2005
Jiali Cui Tieniu Tan Xinwen Hou Yunhong Wang Zhuoshi Wei

In this paper, the authors propose an iris detection method to determine iris existence. The method extracts 4 types of features, i.e., contrast feature, symmetric feature, isotropy feature and disconnected feature. Adaboost is adopted to combine these features to build a strong cascaded classifier. Experiments show that the performance of the method is promising in terms of high speed, accurac...

2007
David Gerónimo Gómez Antonio M. López Daniel Ponsa Angel Domingo Sappa

On–board pedestrian detection is a key task in advanced driver assistance systems. It involves dealing with aspect–changing objects in cluttered environments, and working in a wide range of distances, and often relies on a classification step that labels image regions of interest as pedestrians or non–pedestrians. The performance of this classifier is a crucial issue since it represents the mos...

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