Results 71 to 80 of about 131,003 (284)

A Naive Bayes Source Classifier for X-ray Sources

, 2011
The Chandra Carina Complex Project (CCCP) provides a sensitive X-ray survey of a nearby starburst region over >1 square degree in extent. Thousands of faint X-ray sources are found, many concentrated into rich young stellar clusters. However, significant
Allen, Bazell, Brandt, Broos, Duda, Eric D. Feigelson, Getman, Gordon P. Garmire, Guedel, Harvey, Hastie, Konstantin V. Getman, Leisa K. Townsley, Mahabal, Matthew S. Povich, Norman, Paolillo, Patrick S. Broos, Picaud, Ptak, Ripley, Robitaille, Shemmer, Wolk   +23 more
core   +1 more source

Implementasi Naive Bayes

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.
openaire   +2 more sources

When is the Naive Bayes approximation not so naive? [PDF]

Machine Learning, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Christopher R. Stephens, Hugo Flores Huerta, Ana Ruíz Linares   +2 more
openaire   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

EDUCATIONAL DATA MINING FOR STUDENT ACADEMIC PREDICTION USING K-MEANS CLUSTERING AND NAÏVE BAYES CLASSIFIER

Pilar Nusa Mandiri, 2020
This study proposes the merging of the K-Means clustering data mining method and the Naïve Bayes classifier (K-Means Bayes) for better results in data processing for Student Academic Performance data.
Dewi Ayu Nur Wulandari, Riski Annisa, Lestari Yusuf, Titin Prihatin   +3 more
doaj   +1 more source

Augmented Semi-naive Bayes Classifier

, 2013
The naive Bayes is a competitive classifier that makes strong conditional independence assumptions. Its accuracy can be improved by relaxing these assumptions. One classifier which does that is the semi-naive Bayes. The state-of-the-art algorithm for learning a semi-naïve Bayes from data is the backward sequential elimination and joining (BSEJ ...
Mihaljevic, Bojan, Larrañaga Múgica, Pedro María, Bielza Lozoya, María Concepción   +2 more
openaire   +2 more sources

Explaining Naive Bayes Classifications

Education and Research Archive, 2003
Technical report TR03-09. Naive Bayes classifiers, a popular tool for predicting the labels of query instances, are typically learned from a training set. However, since many training sets contain noisy data, a classifier user may be reluctant to blindly trust a predicted label.
Greiner, Russ, Poulin, B., Lu, Paul, Anvik, J., Lu, Z., Macdonell, Cam, Wishart, David, Eisner, Roman, Szafron, Duane   +8 more
openaire   +3 more sources

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

A New Double Weighted Fuzzy Hypergeometric Naive Bayes Network and its Application for User’s Assessment in Virtual Reality Simulators

International Journal of Computational Intelligence Systems
Assessment methods have been used for identify the quality of procedures performed by human beings. In virtual reality simulators, user’s interaction data can be collected and utilized by Single User Assessment Systems (SUAS) to assess the user’s ...
Jodavid Ferreira, Liliane S. Machado, Ronei Marcos de Moraes   +2 more
doaj   +1 more source