scholarly journals A Frame Work for Classification of Multi Class Medical Data based on Deep Learning and Naive Bayes Classification Model

2020 ◽  
Vol 12 (1) ◽  
pp. 37-43
Author(s):  
N. Ramesh ◽  
◽  
G. Lavanya Devi ◽  
K Srinivasa Rao
Keyword(s):  
Deep Learning ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Medical Data ◽  
Classification Model ◽  
Frame Work ◽  
Naive Bayes Classification ◽  
Naïve Bayes Classification

scholarly journals How are Curiosity and Interest Different? Naïve Bayes Classification of People's Naïve Belief

2020 ◽  
Author(s):  
Ed Donnellan ◽  
Sumeyye Aslan ◽  
Greta M. Fastrich ◽  
Kou Murayama
Keyword(s):  
Information Seeking ◽  
Naive Bayes ◽  
Empirical Work ◽  
Naïve Bayes ◽  
Free Text ◽  
Machine Learning Methods ◽  
Conceptual Clarity ◽  
Naive Bayes Classification ◽  
Naïve Bayes Classification

Researchers studying curiosity and interest note a lack of consensus in whether and how these important motivations for learning are distinct. Empirical attempts to distinguish them are impeded by this lack of conceptual clarity. Following a recent proposal that curiosity and interest are naïve concepts, we sought to determine a naïve consensus view on their distinction using machine learning methods. In Study 1, we demonstrate that there is a naïve consensus in how they are distinguished, by training a Naïve Bayes classification algorithm to distinguish between free-text definitions of curiosity and interest (n = 396 definitions) and using cross-validation to test the classifier on two sets of data (dependent n = 196; independent n = 218). In Study 2, we demonstrate that the naïve consensus is shared by experts and can plausibly underscore future empirical work, as the classifier accurately distinguished definitions provided by experts who study curiosity and interest (n = 92). Our results suggest a shared consensus on the distinction between curiosity and interest, providing a basis for much-needed conceptual clarity facilitating future empirical work. This consensus distinguishes curiosity as more active information-seeking directed towards specific and previously unknown information. In contrast, interest is more pleasurable, in-depth, less momentary information-seeking towards information in domains where people already have knowledge.

Cost-sensitive Naïve Bayes Classification of Uncertain Data

2014 ◽  
Vol 9 (8) ◽  
Author(s):  
Xing Zhang ◽  
Mei Li ◽  
Yang Zhang ◽  
Jifeng Ning
Keyword(s):  
Naive Bayes ◽  
Uncertain Data ◽  
Naïve Bayes ◽  
Naive Bayes Classification ◽  
Naïve Bayes Classification

scholarly journals Naive Bayes Classification of Uncertain Data

2009 ◽  
Author(s):  
Jiangtao Ren ◽  
Sau Dan Lee ◽  
Xianlu Chen ◽  
Ben Kao ◽  
Reynold Cheng ◽  
...  
Keyword(s):  
Naive Bayes ◽  
Uncertain Data ◽  
Naïve Bayes ◽  
Naive Bayes Classification ◽  
Naïve Bayes Classification
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