Results 61 to 70 of about 2,441,680 (241)

Multi‐segments Naïve Bayes classifier in likelihood space

IET Computer Vision, 2018
Naïve Bayes (NB) classifier has shown amazing performance in many real applications. However, the true probability distributions are usually unknown and tend to be quite complicated with high feature dimensions.
Zhenchong Zhao, Xiaodan Wang
doaj   +1 more source

Multi-modal remote sensory learning for multi-objects over autonomous devices

Frontiers in Bioengineering and Biotechnology
IntroductionThere has been an increasing focus on object segmentation within remote sensing images in recent years due to advancements in remote sensing technology and the growing significance of these images in both military and civilian realms.
Aysha Naseer, Naif Almudawi, Hanan Aljuaid, Abdulwahab Alazeb, Yahay AlQahtani, Asaad Algarni, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu   +10 more
doaj   +1 more source

How Accurately Does the Information on Motor Development Collected During Health Checkups for Infants Predict the Diagnosis of Neurodevelopmental Disorders? – A Bayesian Network Model-Based Study

Neuropsychiatric Disease and Treatment, 2022
Yuhei Hatakenaka,1– 3 Koutaro Hachiya,4 Shino Ikezoe,5 Jakob Åsberg Johnels,2 Christopher Gillberg2 1Facuty of Humanities and Social Sciences, University of the Ryukyus, Nishihara, Okinawa, Japan; 2Gillberg Neuropsychiatry Centre, Sahlgrenska Academy ...
Hatakenaka Y, Hachiya K, Ikezoe S, Åsberg Johnels J, Gillberg C   +4 more
doaj  

A nomogram for P values

BMC Medical Research Methodology, 2010
Background P values are the most commonly used tool to measure evidence against a hypothesis. Several attempts have been made to transform P values to minimum Bayes factors and minimum posterior probabilities of the hypothesis under consideration ...
Held Leonhard
doaj   +1 more source

Differentially private posterior summaries for linear regression coefficients

The Journal of Privacy and Confidentiality, 2018
In Bayesian regression modeling, often analysts summarize inferences using posterior probabilities and quantiles, such as the posterior probability that a coefficient exceeds zero or the posterior median of that coefficient.
Gilad Amitai, Jerome Reiter
doaj   +1 more source

Failure Diagnosis Analysis of Medical Equipment Based on Fault Tree and Fuzzy Bayesian Network

Zhongguo yiliao qixie zazhi
ObjectiveTo enhance the reliability of medical equipment, this study aims to develop a failure cause diagnosis model and provide rational suggestions for efficient equipment use.
Ke ZHANG, Liang HUANG
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Détente: A Practical Understanding of P values and Bayesian Posterior Probabilities [PDF]

, 2020
Stephen J. Ruberg
openalex   +1 more source

Using Bayesian statistics to estimate the likelihood a new trial will demonstrate the efficacy of a new treatment

BMC Medical Research Methodology, 2017
Background The common frequentist approach is limited in providing investigators with appropriate measures for conducting a new trial. To answer such important questions and one has to look at Bayesian statistics.
David J. Biau, Samuel Boulezaz, Laurent Casabianca, Moussa Hamadouche, Philippe Anract, Sylvie Chevret   +5 more
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Item-Fit Statistic Based on Posterior Probabilities of Membership in Ability Groups

, 2022
Bartosz Kondratek
openalex   +2 more sources

Bayesian posterior probabilities: revisited

, 2010
7 pages, including 3 ...
openaire   +2 more sources