نتایج جستجو برای: bayesian classifier

تعداد نتایج: 122173  

Journal: :Pattern Recognition Letters 2003
Franz Pernkopf Paul O'Leary

This paper presents a floating search approach for learning the network structure of Bayesian network classifiers. A Bayesian network classifier is used which in combination with the search algorithm allows simultaneous feature selection and determination of the structure of the classifier. The introduced search algorithm enables conditional exclusions of previously added attributes and/or arcs...

Journal: :International Journal of Computer Applications 2011

Journal: :Journal of physics 2023

Abstract The enormous computing tasks in the Mobile Edge Computing (MEC) beget challenges correlated with cost, energy consumption and quality of service. However, existing studies are not optimized enough for MEC terms selection task classification scheduling schemes. Inspired by spam idea, a novel scheme is proposed via Bayesian Classifier. first categorized into three priority categories usi...

2003
Jesús Cerquides Ramon López de Mántaras

The Naive Bayes classifier is a simple and accurate classifier. This paper shows that assuming the Naive Bayes classifier model and applying Bayesian model averaging and the principle of indifference, an equally simple, more accurate and theoretically well founded classifier can be obtained. Introduction In this paper we use Bayesian model averaging and the principle of indifference to derive a...

Journal: :Pattern Recognition 2013
Lori A. Dalton Edward R. Dougherty

In part I of this two-part study, we introduced a new optimal Bayesian classification methodology that utilizes the same modeling framework proposed in Bayesian minimum-mean-square error (MMSE) error estimation. Optimal Bayesian classification thus completes a Bayesian theory of classification, where both the classifier error and our estimate of the error may be simultaneously optimized and stu...

Journal: :Journal of computer-aided molecular design 2014
Zhihong Liu Minghao Zheng Xin Yan Qiong Gu Johann Gasteiger Johan Tijhuis Peter Maas Jiabo Li Jun Xu

Predicting compound chemical stability is important because unstable compounds can lead to either false positive or to false negative conclusions in bioassays. Experimental data (COMDECOM) measured from DMSO/H2O solutions stored at 50 °C for 105 days were used to predicted stability by applying rule-embedded naïve Bayesian learning, based upon atom center fragment (ACF) features. To build the n...

2016
S. Urmela Yan Li

Distributed Data Mining (DDM) has become one of the promising areas of Data Mining. DDM techniques include classifier approach and agent-approach. Classifier approach plays a vital role in mining distributed data, having homogeneous and heterogeneous approaches depend on data sites. Homogeneous classifier approach involves ensemble learning, distributed association rule mining, meta-learning an...

Journal: :JSW 2011
Tao Dong Wenqian Shang Haibin Zhu

Text categorization is a fundamental methodology of text mining and a hot topic of the research of data mining and web mining in recent years. It plays an important role in building traditional information retrieval, web indexing architecture, Web information retrieval, and so on. This paper presents an improved algorithm of text categorization that combines the feature weighting technique with...

2008
Chunping Wang Xuejun Liao Lawrence Carin David B. Dunson

A non-parametric hierarchical Bayesian framework is developed for designing a sophisticated classifier based on a mixture of simple (linear) classifiers. Each simple classifier is termed a local “expert”, and the number of experts and their construction are manifested via a Dirichlet process formulation. The simple form of the “experts” allows direct handling of incomplete data. The model is fu...

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