Results 121 to 130 of about 60,977 (298)
Spam Filtering with Naive Bayes -- Which Naive Bayes?
, 2006 Naive Bayes is very popular in commercial and open-source anti-spam e-mail filters. There are, however, several forms of Naive Bayes, something the anti-spam literature does not always acknowledge.
Vangelis Metsis, et al.
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Fire and Materials, EarlyView.ABSTRACT The relationship between accidental dwelling fire incidence and fire injury and fatality was examined using a Bayesian model to estimate the probability of a fire injury or fatality resulting from an accidental dwelling fire incidence under different circumstances of fire incidence (type of accidental dwelling fire, dwelling occupancy type ...
M. Taylor +5 more
wiley +1 more source
IET Networks, EarlyView., 2022 Abstract Everything can be connected in the Internet of Things (IoTs) technology that enables efficient communication between connected objects. IoTs industry‐based meta‐heuristic and mining algorithms, which are considered an important field of Artificial Intelligence will be used to construct a healthcare application in this study for lowering costs,
Muhaned Al‐Hashimi +4 more
wiley +1 more source
Classification : Naive Bayes Dengan Python
, 2020 Data Mining Materi ini berisikan link video bagaimana membuat pemrograman classification naive bayes dengan ...
Nursikuwagus, Agus
core +1 more source
Improved incremental algorithm of Naive Bayes
Tongxin xuebao, 2016 A novel Naive Bayes incremental algorithm was proposed,which could select new features.For the incremental sample selection of the unlabeled corpus,a minimum posterior probability was designed as the double threshold of sample selection by using the ...
Shui-fei ZENG +3 more
doaj +2 more sources
Journal of Biostatistics and Epidemiology, 2018 Background & Aim: Clustering is the method of classifying discrete data such as Kmodes, and Naïve Bayes classifier is the classification to predict the unknown real classes.
Zahra Zamaninasab +2 more
doaj
Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models
Journal of Forecasting, EarlyView.ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly +2 more
wiley +1 more source
Intent Arabic text categorisation based on different machine learning and term frequency
IET Networks, EarlyView., 2022 Abstract The complexity of Internet network configurations has made managing networks a complicated undertaking. Intent‐Based Networking (IBN) is a potential solution to this issue. In contrast to conventional networks, where a concrete description of the settings typically conveys a network administrator's goal kept on each device, an administrator's ...
Mohammad Fadhil Mahdi +1 more
wiley +1 more source
Combining Naive Bayes and Decision Tables
, 2008 We investigate a simple semi-naive Bayesian ranking method that combine naive Bayes with induction of decision tables. Naive Bayes and decision tables can both be trained efficientyly, and the same holds true for the combined semi-naive model.
Hall, Mark A. +3 more
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Extended Naive Bayes for group based classification
, 2014 This paper focuses on extending Naive Bayes classifier to address group based classification problem. The group based classification problem requires labeling a group of multiple instances given the prior knowledge that all the instances of the group ...
Bradley, Andrew P. +5 more
core +1 more source