Results 21 to 30 of about 161,172 (233)
Bayesian Logistic Regression Model for Sub-Areas
Stats, 2023 Many population-based surveys have binary responses from a large number of individuals in each household within small areas. One example is the Nepal Living Standards Survey (NLSS II), in which health status binary data (good versus poor) for each ...
Lu Chen, Balgobin Nandram
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Maximal Uncorrelated Multinomial Logistic Regression
IEEE Access, 2019 Multinomial logistic regression (MLR) has been widely used in the field of face recognition, text classification, and so on. However, the standard multinomial logistic regression has not yet stressed the problem of data redundancy.
Dajiang Lei +4 more
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TRANSFER LEARNING BASED ON LOGISTIC REGRESSION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 In this paper we address the problem of classification of remote sensing images in the framework of transfer learning with a focus on domain adaptation.
A. Paul, F. Rottensteiner, C. Heipke
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Privacy-preserving logistic regression with secret sharing
BMC Medical Informatics and Decision Making, 2022 Background Logistic regression (LR) is a widely used classification method for modeling binary outcomes in many medical data classification tasks. Researchers that collect and combine datasets from various data custodians and jurisdictions can greatly ...
Ali Reza Ghavamipour +2 more
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Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
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Multicollinearity in Logistic Regression Model -Subject Review- [PDF]
المجلة العراقية للعلوم الاحصائية, 2020 : The logistic regression model is one of the modern statistical methods developed to predict the set of quantitative variables (nominal or monotonous), and it is considered as an alternative test for the simple and multiple linear regression ...
Najlaa Saad Ibrahim +2 more
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Leukemia prediction using sparse logistic regression.
PLoS ONE, 2013 We describe a supervised prediction method for diagnosis of acute myeloid leukemia (AML) from patient samples based on flow cytometry measurements. We use a data driven approach with machine learning methods to train a computational model that takes in ...
Tapio Manninen +3 more
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Prediksi Potensi Donatur Menggunakan Model Logistic Regression
Indonesian Journal of Data and Science, 2023 GRDS menghadapi kelangkaan dana, ketika diperlukan untuk merawat para korban Gaja. Gaja adalah topan bernama kelima dari musim siklon Samudra Hindia Utara 2018 yang mempengaruhi sebagian besar tempat di Tamil Nadu, India selama bulan November 2018 ...
sitti rahmah jabir +3 more
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Uncertain logistic regression models
AIMS MathematicsLogistic regression is a generalized nonlinear regression analysis model and is often used for data mining, automatic disease diagnosis, economic prediction, and other fields.
Jinling Gao , Zengtai Gong
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Advanced Materials Interfaces, EarlyView., 2023 This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi +4 more
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