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Naive Bayes classifier
Known as:
Bayesian Classifiers
, Naive-Bayes
, Naïve Bayesian classification
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In machine learning, naive Bayes classifiers are a family of simple probabilistic classifiers based on applying Bayes' theorem with strong (naive…
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Activity recognition
Additive smoothing
Algorithm
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Broader (1)
Statistical classification
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2014
Highly Cited
2014
Bangla news classification using naive Bayes classifier
Abu Nowshed Chy
,
M. Seddiqui
,
Sowmitra Das
16th Int'l Conf. Computer and Information…
2014
Corpus ID: 15205628
Web is gigantic and being constantly update. Bangla news in web are rapidly grown in the era of information age where each news…
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2013
2013
Self-adaptive probability estimation for Naive Bayes classification
Jia Wu
,
Z. Cai
,
Xingquan Zhu
IEEE International Joint Conference on Neural…
2013
Corpus ID: 9064476
Probability estimation from a given set of training examples is crucial for learning Naive Bayes (NB) Classifiers. For an…
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2013
2013
NAÏVE BAYES CLASSIFIER DAN SUPPORT VECTOR MACHINES UNTUK SENTIMENT ANALYSIS
Ni Wayan
,
Sumartini Saraswati
,
S. Prodi
,
Teknik Informatika
2013
Corpus ID: 60475287
Text mining refers to the process of deriving high-quality information from text. High-quality information is typically derived…
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2012
2012
Layered approach for intrusion detection using naïve Bayes classifier
Neelam Sharma
,
S. Mukherjee
International Conference on Advances in Computing…
2012
Corpus ID: 1027426
Intrusion detection is the process of monitoring and analyzing the events occurring in a computer system in order to detect signs…
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2010
2010
Naive Bayes Classifier based Arabic document categorization
Hatem M. Noaman
,
S. Elmougy
,
Ahmed Ghoneim
,
T. Hamza
GI-Fachtagung Informatik und Schule
2010
Corpus ID: 17200867
Text Categorization aims to assign an electronic document to one or more categories based on its contents. Due to the rapid…
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2010
2010
Naive Bayes Classifier for Positive Unlabeled Learning with Uncertainty
Jiazhen He
,
Yang Zhang
,
Xue Li
,
Yong Wang
SDM
2010
Corpus ID: 11944146
Existing algorithms for positive unlabeled learning (PU learning) only work with certain data. However, data uncertainty is…
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2007
2007
Robust Approach for Estimating Probabilities in Naive-Bayes Classifier
B. Chandra
,
Manish Gupta
,
M. Gupta
Pattern Recognition and Machine Intelligence
2007
Corpus ID: 206735888
Naive-Bayes classifier is a popular technique of classification in machine learning. Improving the accuracy of naive-Bayes…
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Highly Cited
2007
Highly Cited
2007
Alteration of submarine basaltic glass from the Ontong Java Plateau: A STXM and TEM study
K. Benzerara
,
N. Menguy
,
N. Banerjee
,
T. Tyliszczak
,
G. Brown
,
F. Guyot
2007
Corpus ID: 53340660
2006
2006
Modified Naïve Bayes Classifier for E-Catalog Classification
Young-gon Kim
,
Taehee Lee
,
Jonghoon Chun
,
Sang-goo Lee
DEECS
2006
Corpus ID: 1264362
As the wide use of online business transactions, the volume of product information that needs to be managed in a system has…
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Highly Cited
2004
Highly Cited
2004
Naive Bayes Classifiers That Perform Well with Continuous Variables
R. Bouckaert
Australian Conference on Artificial Intelligence
2004
Corpus ID: 37154569
There are three main methods for handling continuous variables in naive Bayes classifiers, namely, the normal method (parametric…
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