Results 21 to 30 of about 1,921,898 (301)
Loan classification using logistic regression
Informatika, 2023 Objectives. The studied problem of loan classification is particularly important for financial institutions, which must efficiently allocate monetary assets between entities as part of the provision of financial services.
U. I. Behunkou, M. Y. Kovalyov
doaj +1 more source
ReLogit: Rare Events Logistic Regression
Journal of Statistical Software, 2003 We study rare events data, binary dependent variables with dozens to thousands of times fewer ones (events, such as wars, vetoes, cases of political activism, or epidemiological infections) than zeros ("nonevents").
Michael Tomz, Gary King, Langche Zeng
doaj +3 more sources
Privacy-preserving logistic regression training
BMC Medical Genomics, 2018 Background Logistic regression is a popular technique used in machine learning to construct classification models. Since the construction of such models is based on computing with large datasets, it is an appealing idea to outsource this computation to a
Charlotte Bonte, Frederik Vercauteren
doaj +1 more source
Predicting Heart Disease using Logistic Regression
Knowledge Engineering and Data Science, 2022 A common risk of death is caused by heart disease. It is critical in the field of medicine to be able to diagnose cardiac disease in order to adequately prevent and treat patients.
Mochammad Anshori, M. Syauqi Haris
doaj +1 more source
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
wiley +1 more source
Fuzzy Semi-Parametric Logistic Quantile Regression Model
Wasit Journal for Pure Sciences, 2023 In this paper, the fuzzy semi-parametric logistic quantile regression model was studied in the absence of special conditions in the classical regression models.
Ahmed Razzaq, Ayad H. shemaila
doaj +1 more source
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
doaj +1 more source
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
wiley +1 more source
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
doaj +1 more source
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
doaj +1 more source