165 articles for “Logistic”

Review ArticleOpen accessEvery word in the titleEgg Consumption among Young People: A Study through the Application of the Logistic Regression ModelCarlo Giannetto, Angela Alibrandi, Agata Zirilli, Maurizio LanfranchiThe purpose of the present survey is to study and to investigate the proper eating style, focusing the attention on the propensity to “egg” consumption, in the diet of young people, with reference to the students attending the University of Messina. The data collection technique that was used consisted of the administration of a distributed anonymous ad hoc questionnaire by … …American Journal of Applied Sciences, Vol. 13, Issue 6 · 24 Jun 2016 · 7,290 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleMeasures of Explained Variation and the Base-Rate Problem for Logistic RegressionDinesh Sharma, Dan McGee, B.M. Golam KibriaProblem statement: Logistic regression, perhaps the most frequently used regression model after the General Linear Model (GLM), is extensively used in the field of medical science to analyze prognostic factors in studies of dichotomous outcomes. Unlike the GLM, many different proposals have been made to measure the explained variation in logistic regression analysis. One of the limitations of these measures … …Current Research in Biostatistics, Vol. 2, Issue 1 · 25 Feb 2012 · 8,576 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleRobust Logistic Regression to Static Geometric Representation of RatiosAlireza Bahiraie, Noor Akma Ibrahim, A.K.M. Azhar, Ismail Bin MohdProblem statement: Some methodological problems concerning financial ratios such as non-proportionality, non-asymetricity, non-salacity were solved in this study and we presented a complementary technique for empirical analysis of financial ratios and bankruptcy risk. This new method would be a general methodological guideline associated with financial data and bankruptcy risk. Approach: We proposed the use of a new measure of risk, … …Journal of Mathematics and Statistics, Vol. 5, Issue 3 · 30 Sep 2009 · 8,216 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleThe Estimation of Logistic Probability Model of Binomial Data: Simulation ComparisonZaki. J. Al- Sarraf, Faris M. Al- Athari, Hilmi F. KittaniProperties of various types of estimators of the regression coefficients in linear logistic regression models were considered. The estimators include those based on maximum likelihood, minimum chi-square and weighted least squares. The results of a large scale simulation investigation evaluating the moment properties of the estimators are presented for the case of logistic model with a single explanatory variable. …Journal of Mathematics and Statistics, Vol. 4, Issue 2 · 30 Jun 2008 · 6,690 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleReal Time Object Tracking and Protection: Hybrid Logistics Architecture in Ubiquitous Environments (HLAiUE)Abdul Jawwad Patel, Abeer Alsadoon, P.W.C. Prasad, A. ElchouemiRealtime object security and vehicle tracking have not been successfully implemented in commercial vehicles due to limitations in processing large amount of data and hardware capabilities. This paper aimed to improve the object security, processing power and data storage in a distributed environment. The proposed system (HLAiUE) consists of a three-layer architecture, first layer is used to collect data, second … …American Journal of Applied Sciences, Vol. 15, Issue 8 · 17 Oct 2018 · 7,520 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsEarly Diagnosis of Parkinson's Disease Through Voice Analysis and Machine LearningAmrita Naik, Mohd Sahil Khan, Akhilesh Manoj Saraf et al.Parkinson’s Disease (PD) is a progressive neurological disorder, and its prevalence has increased considerably in recent years. Early and accurate diagnosis plays a crucial role in effective treatment, but identifying the disease in its early stages remains challenging, especially for non-specialist clinicians. This study presents a predictive analytics framework for detecting Parkinson's disease using voice-based features. To improve the diversity … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 637 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsApplication of Machine Learning for the Detection of Depression and Mindfulness as a Mitigation MethodSantiago Domingo Moquillaza Henriquez, Liliana Ruth Huamán Rondón et al.Depression is a global mental health problem with various causes. Nowadays, with Artificial Intelligence, it can be predicted in order to take preventive measures, whether at a psychotherapeutic or pharmacological level. This research, based on a survey conducted, detects depression using logistic regression with a 91% fit to the ROC-AUC model, accuracy of 0.839188, precision 0.851354. In addition, a study … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,216 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsEvaluation of Machine Learning Models to Predict Student Academic Performance Using Structured Educational DataHardik Ishwarbhai Patel, Dharmendra PatelThis study analyses the use of machine learning for predicting the academic performance of students using their academic information from the institution, combined with socio-economic information that comes from outside sources. The collection of information is done using structured questionnaires as well as through data extraction from the Student Information System (SIS). To increase the reliability of models built, a … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,419 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsDeveloping an Effective Churn Prediction Model for Telecommunications: Enhancing Customer Retention through Advanced Machine Learning TechniquesAshu Goyal, Anuj Gupta, Sharad Kumar et al.Customer churn poses a significant challenge for the telecommunications sector, resulting in substantial revenue losses and increased customer acquisition costs. This research creates an efficient churn prediction model that combines state-of-the-art machine learning with ensemble learning to maximize customer retention. With the IBM Telco Customer Churn dataset, several baseline models, including Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and Support … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 3,164 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsPredicting Financial Statement Failure of Listed Firms in Market for Alternative Investment (mai) using Machine LearningPattanapong Kumsin, Salakjit Ninlaphay, Anupong SukprasertThe purpose of this research is to investigate the financial ratios of companies listed on the Market for Alternative Investment (mai) in Thailand, as well as the likelihood of these companies' financial statement failure. It also intends to create a financial statement failure predicting model for companies listed on the mai and assess the performance of various forecasting models using … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,240 accessesView PDF Cite