Results 1 to 10 of about 123,621 (240)
Exact Learning Augmented Naive Bayes Classifier. [PDF]
Entropy (Basel), 2021 Earlier studies have shown that classification accuracies of Bayesian networks (BNs) obtained by maximizing the conditional log likelihood (CLL) of a class variable, given the feature variables, were higher than those obtained by maximizing the marginal likelihood (ML).
Sugahara S, Ueno M.
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Contextualizing Naive Bayes Predictions [PDF]
Information Processing and Management of Uncertainty in Knowledge-Based Systems18th International Conference, 2020 A classification process can be seen as a set of actions by which several objects are evaluated in order to predict the class(es) those objects belong to. In situations where transparency is a necessary condition, predictions resulting from a classification process are needed to be interpretable.
Loor M, De Tré G.
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Parsimonious Naive Bayes [PDF]
Annals of Computer Science and Information Systems, 2014 We describe our submission to the AAIA′14 Data Mining Competition, where the objective was to reach good predictive performance on text mining classification problems while using a small number of variables. Our submission was ranked 6th, less than 1% behind the winner.
Clérot, Fabrice, Boullé, Marc
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Improving Usual Naive Bayes Classifier Performances with Neural Naive Bayes based Models
Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods, 2022 Naive Bayes is a popular probabilistic model appreciated for its simplicity and interpretability. However, the usual form of the related classifier suffers from two major problems. First, as caring about the observations' law, it cannot consider complex features.
Azeraf, Elie +2 more
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Bayes and Naive Bayes Classifier
, 2014 The Bayesian Classification represents a supervised learning method as well as a statistical method for classification. Assumes an underlying probabilistic model and it allows us to capture uncertainty about the model in a principled way by determining probabilities of the outcomes.
Vikramkumar, B, Vijaykumar, Trilochan
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INTELIGENCIA ARTIFICIAL, 2006 Naive Bayes is a well-known and studied algorithm both in statistics and machine learning. Bayesian learning algorithms represent each concept with a single probabilistic summary. This paper presents a variant of the Naive Bayes method, in which the original training set is augmented in the following fashion: Leave-One-Out procedure is applied over the
J.M. Martinez-Otzeta +4 more
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Lyrics classification using Naive Bayes
2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2018 Text classification is an important and common task in supervised machine learning. The Naive Bayes Classifier is a popular algorithm that can be used for this purpose. The goal of our research was prediction of song performer using Naive Bayes classification algorithm based solely on lyrics. A dataset that has been created consists of lyrics performed
Bužić, Dalibor, Dobša, Jasminka
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Directional naive Bayes classifiers [PDF]
Pattern Analysis and Applications, 2013 Directional data are ubiquitous in science. These data have some special properties that rule out the use of classical statistics. Therefore, different distributions and statistics, such as the univariate von Mises and the multivariate von Mises–Fisher distributions, should be used to deal with this kind of information.
López Cruz, Pedro Luis +2 more
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Naive Bayes Classification of Uncertain Data [PDF]
2009 Ninth IEEE International Conference on Data Mining, 2009 Traditional machine learning algorithms assume that data are exact or precise. However, this assumption may not hold in some situations because of data uncertainty arising from measurement errors, data staleness, and repeated measurements, etc. With uncertainty, the value of each data item is represented by a probability distribution function (pdf). In
Lee, SD +5 more
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Journal of Informatics, Information System, Software Engineering and Applications (INISTA), 2019 Perkembangan sektor industri yang semakin pesat dalam memenuhi kebutuhan hidup setiap harinya membutuhkan bahan kimia sebagai bahan utama dalam proses suatu produksi. Tidak sedikit dari bahan kimia tersebut mengandung zat berbahaya dan beracun yang dapat menimbulkan efek yang sangat membahayakan bagi lingkungan dan manusia.
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