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30 articles for “decision trees”

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Research ArticleOpen accessPhrase in the titleObesity Level Estimation Software based on Decision TreesEduardo De-La-Hoz-Correa, Fabio E. Mendoza-Palechor, Alexis De-La-Hoz-Manotas et al.Obesity has become a global epidemic that has doubled since 1980, with serious consequences for health in children, teenagers and adults. Obesity is a problem has been growing steadily and that is why every day appear new studies involving children obesity, especially those looking for influence factors and how to predict emergence of the condition under these factors. In this … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 14,100 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAntibiogram-Derived Radial Decision Trees: An Innovative Approach to Susceptibility Data DisplayRocco J. Perla, Paul P. BelliveauHospital antibiograms (ABGMs) are often presented in the form of large 2-factor (single organism vs. single antimicrobial) tables. Presenting susceptibility data in this fashion, although of value, does have limitations relative to drug resistant subpopulations. As the crisis of antimicrobial drug-resistance continues to escalate globally, clinicians need (1) to have access to susceptibility data that, for isolates resistant to first-line … …American Journal of Infectious Diseases, Vol. 1, Issue 2 · 30 Jun 2005 · 6,502 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAnalysis of Decision Trees in Context Clustering of Hidden Markov Model Based Thai Speech SynthesisSuphattharachai ChomphanProblem statement: In Thai speech synthesis using Hidden Markov model (HMM) based synthesis system, the tonal speech quality is degraded due to tone distortion. This major problem must be treated appropriately to preserve the tone characteristics of each syllable unit. Since tone brings about the intelligibility of the synthesized speech. It is needed to establish the tone questions and other … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 6,844 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMachine Learning Approaches for the Prediction of Gas Turbine TransientsArnaud Nguembang Fadja, Giuseppe Cota, Francesco Bertasi et al.Gas Turbine (GT) emergency shutdowns can lead to energy production interruption and may also reduce the lifespan of a turbine. In order to remain competitive in the market, it is necessary to improve the reliability and availability of GTs by developing predictive maintenance systems that are able to predict future conditions of GTs within a certain time. Predicting such situations … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 7,660 accessesView PDFCite
Review ArticleOpen accessIn the keywordsCrime Prediction Using Machine Learning: A Comparative AnalysisAbdulrahman Alsubayhin, Muhammad Ramzan, Bander AlzahraniIn the past few years, Machine Learning (ML) methods have acquired extensive attention from researchers and even criminology practitioners for their potential in crime prediction and crime forecast. To date, many research studies have already been performed on crime prediction using machine learning techniques. Some common methods that have been used include KNNs, Decision trees, Naïve Bayes, and random forest, … …Journal of Computer Science, Vol. 19, Issue 9 · 29 Aug 2023 · 8,063 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPredicting Students’ Academic Performance in the University Using Meta Decision Tree ClassifiersShanthini A., G. Vinodhini, R.M. ChandrasekaranStudent performance prediction is an area of concern for educational institutions. At the University level learning system, the method or rule adopted to identify the candidates who pass or fail differs depending on various factors such as the course, the department of study and so on. Predicting the result of a student in a course is an issue that has … …Journal of Computer Science, Vol. 14, Issue 5 · 28 Feb 2018 · 9,194 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comparative Study of Data Mining approaches for Bag of Visual Words Based Image ClassificationSahar Abd El Hameed Mokhtar, Heba Ahmed ElnemrImage classification is one of the most significant and challenging tasks in computer vision. The goal of this task is to build a system that is capable to reveal an image label within a collection of different image categories. This paper presents and discusses the application of various data mining techniques for image classification based on Bag of Visual Words … …Journal of Computer Science, Vol. 14, Issue 1 · 12 Jan 2018 · 7,983 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comparison between Different Data Mining Algorithms in Freight Mode ChoiceAmir Samimi, Hesamoddin Razi-Ardakani, Amir NohekhanThis research aims to study application of support vector machine algorithm, artificial neural networks and five different types of decision trees in predicting mode choice of freight transportation. Performance of these models has been compared with log it model which is one the most prevalent statistical models in the field. Effect of factors such as cargo weight, distance, type and … …American Journal of Applied Sciences, Vol. 14, Issue 2 · 5 Feb 2017 · 7,623 accessesView PDFCite
Research ArticleOpen accessIn the keywordsChildhood Cancer-a Hospital based study using Decision Tree TechniquesK. Kalaivani, R. ShanmugalakshmiProblem statement: Cancer is generally regarded as a disease of adults. But there being a higher proportion of childhood cancer (ALL-Acute Lymphoblastic Leukemia) in India. The incidence of childhood cancer has increased over the last 25 years, but the increase is much larger in females. The aim was to increase our understanding of the determinants of south Indian parental reactions … …Journal of Computer Science, Vol. 7, Issue 12 · 17 Oct 2011 · 7,057 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMapping Learning Algorithms on Data, a Useful Step for Optimizing Performances and Their ComparisonFilippo NeriIn this paper, we propose a novel methodology to map learning algorithms on data (performance map) in order to gain more insights into the distribution of their performances across their parameter space. This methodology provides useful information when selecting a learner's best configuration for the data at hand and it also enhances the comparison of learners across learning contexts. In … …Journal of Computer Science, Vol. 20, Issue 9 · 10 Jul 2024 · 4,501 accessesView PDFCite