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98 results for “Logistic Regression (LR)”
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Research ArticleOpen accessIn the keywordsConsumer Choice Prediction: Artificial Neural Networks versus Logistic ModelsChristopher Gan, Visit Limsombunchai, Mike Clemes, Amy WengConventional econometric models, such as discriminant analysis and logistic regression have been used to predict consumer choice. However, in recent years, there has been a growing interest in applying artificial neural networks (ANN) to analyse consumer behaviour and to model the consumer decision-making process. The purpose of this paper is to empirically compare the predictive power of the probability neural … …Journal of Social Sciences, Vol. 1, Issue 4 · 31 Dec 2005 · 8,441 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Analysis of Credit Scoring for Agricultural Loans in ThailandVisit Limsombunchai, Christopher Gan, Minsoo LeeLoan contract performance determines the profitability and stability of the financial institutions and screening the loan applications is a key process in minimizing credit risk. Before making any credit decisions, credit analysis (the assessment of the financial history and financial backgrounds of the borrowers) should be completed as part of the screening process. A good credit risk assessment assists financial … …American Journal of Applied Sciences, Vol. 2, Issue 8 · 31 Aug 2005 · 7,620 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComparison of Probability Curves Obtained from 2 Quantitative Allergen-specific IgE Assays: FEIA and 3gAllergyTMT. M. Li, T. Chuang, S. M. Li, D. Hovanec-BurnsThe validity and benefit of probability curves in allergen-specific IgE (sIgE) testing and their applicability to more than a few allergens are still pending. One study[1] presented probability curves for 4 food allergens and proposed decision points to rule out the need for food challenges in his clinic. Since then, such cutoffs were reported by Boyano-Martinez[2] to be dependent on … …American Journal of Immunology, Vol. 1, Issue 2 · 30 Jun 2005 · 6,737 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSentence Classification Using Attention Model for E-Commerce Product ReviewNagendra N, Chandra JThe importance of aspect extraction in text classification, particularly in the e-commerce sector. E-commerce platforms generate vast amounts of textual data, such as comments, product descriptions, and customer reviews, which contain valuable information about various aspects of products or services. Aspect extraction involves identifying and classifying individual traits or aspects mentioned in textual reviews to understand customer opinions, improve products, … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 5,855 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIoT Intrusion Detection using Auto-Encoder and Machine Learning TechniquesAhmed Ridha Khudhu, Khairulmizam SamsudinIoTnetwork refers to the capability of connecting smart and various devices to asingle network for the sake of performing a particular task. Similar toconventional networks, IoT networks are vulnerable to several attacks.Therefore, IoT Intrusion Detection has caught much research attention. Severalstudies have examined the task of intrusion detection for IoT networks. Withinsuch studies, the focus was set to accommodate a … …Journal of Computer Science, Vol. 18, Issue 10 · 27 Sep 2022 · 6,458 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSentimental Analysis on Health-Related Information with Improving Model Performance using Machine LearningWael M.S. Yafooz, Abdullah AlsaeediSocial media platforms are extensively used in exchanging and sharing information and user experience, thereby resulting in massive outspread and viewing of personal experiences in many fields of life. Thus, informative health-related videos on YouTube are highly perceptible. Many users tend to procure medical treatments and health-related information from social media particularly from YouTube when searching for chronic illness treatments. … …Journal of Computer Science, Vol. 17, Issue 2 · 22 Feb 2021 · 7,460 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMultilevel Ordinal Response Modeling of Trend of Breastfeeding InitiationWaheed Babatunde Yahya, Samson Babatunde AdebayoThe amount of health benefits derived from breastfeeding is influenced by age of the child at initiation of the first breast milk, the duration and intensity of breastfeeding and age at which the child is introduced to supplementary foods and other liquids. In this study, the general trend of timing of breastfeeding initiation among nursing mothers in Nigeria between 1990 … …Current Research in Biostatistics, Vol. 3, Issue 1 · 4 Sep 2013 · 8,157 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe Empirical Study of Japanese Deposit Withdrawal Behaviors on Unstable Financial EnvironmentToshihiko Takemura, Takashi Kozu, Tetsuro KobayashiProblem statement: We need to analyze to withdrawal behavior rather than deposit behavior on the situation which financial institutions might fail. However, there are few studies on withdrawal behavior although there are various studies on individual deposit behavior. Approach: Our purpose of this study is to investigate relationships between individual’s deposit withdrawal behavior and economic and psychological factors using micro … …American Journal of Economics and Business Administration, Vol. 3, Issue 2 · 7 Apr 2011 · 6,992 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Based Prediction of Catch Yields in Small Scale FisheriesEpifelward Niño Olaivar Amora, Patrick D. CernaSmall-scale fisheries are critical for food security and livelihoods but increasingly face threats from overfishing and environmental change. This study employed machine learning to predict catch yields in Cogtong Bay, Philippines, using 3,478 records collected in 2020–2021 that included species, gear, location, season, and weather data. Models developed in Python with scikit-learn and XGBoost compared Random Forest (RF), Extreme Gradient … …Journal of Computer Science, Vol. 22, Issue 8 · 24 Aug 2026 · 1,096 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Corporate Financial Distress Using Explainable Machine Learning: Implications for Risk Management TechnologyKanjana Hinthaw, Warawut NarkbunnumFinancial distress prediction is a critical task in financial risk management, yet it remains challenging due to class imbalance, complex financial structures, and limited model interpretability. This study develops an integrated machine learning framework that combines feature selection, class imbalance handling, threshold optimization, and Explainable Artificial Intelligence (XAI) to improve both predictive performance and decision-making reliability. Using a dataset of … …Journal of Computer Science, Vol. 22, Issue 7 · 22 Jul 2026 · 1,130 accessesView PDFCite