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23 results for “decision tree data mining”

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Research ArticleOpen accessIn the abstractFuzzy Modeled K-Cluster Quality Mining of Hidden Knowledge for Decision SupportS. Parkash Kumar, K. S. RamaswamiProblem statement: The work presented Fuzzy Modeled K-means Cluster Quality Mining of hidden knowledge for Decision Support. Based on the number of clusters, number of objects in each cluster and its cohesiveness, precision and recall values, the cluster quality metrics is measured. The fuzzy k-means is adapted approach by using heuristic method which iterates the cluster to form an efficient … …Journal of Computer Science, Vol. 7, Issue 11 · 24 Aug 2011 · 6,671 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of CART Algorithm in Blood Donors ClassificationT. Santhanam, Shyam SundaramProblem statement: This study used data mining modeling techniques to examine the blood donor classification. The availability of blood in blood banks is a critical and important aspect in a healthcare system. Blood banks (in the developing countries context) are typically based on a healthy person voluntarily donating blood and is used for transfusions or made into medications. The ability … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 8,624 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring Spatial ARM (Spatial Association Rule Mining) for Geo-Decision Support SystemRanjana Vyas, Lokesh Kumar Sharma, U. S. TiwaryGeographical Decision Support System (Geo-DSS) is a demanding field, since enormous amount of spatial data have been collected in various applications, ranging form Remote Sensing to GIS, Computer Cartography, Environmental Assessment and Planning. Although some efforts were made to combine spatial mining with Spatial Decision Support System but mostly researchers for spatial database are using a popular data mining approach-Apriori … …Journal of Computer Science, Vol. 3, Issue 11 · 30 Nov 2007 · 6,956 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmpirical Study on Applications of Data Mining Techniques in HealthcareHarleen Kaur, Siri Krishan WasanThe healthcare environment is generally perceived as being ‘information rich’ yet ‘knowledge poor’. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. Knowledge discovery and data mining have found numerous applications in business and scientific domain. Valuable knowledge can be discovered … …Journal of Computer Science, Vol. 2, Issue 2 · 28 Feb 2006 · 9,834 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAnalysis of Student Mental Health Dataset Using Mining TechniquesYemima Monica Geasela, Devi Yurisca Bernanda, Johanes Fernandes Andry et al.This study utilizes a decision tree model in RapidMiner to analyze a dataset from Kaggle, comprising 200 student records. Among these, 70 students reported mental health issues, while 130 did not. Strikingly, a significant majority of 58 out of the 70 students with mental health concerns do not seek assistance from professionals. This study underscores the pressing issue of underutilization … …Journal of Computer Science, Vol. 20, Issue 1 · 22 Dec 2023 · 6,963 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordClassify Breast Cancer Patients using Hybrid Data-Mining TechniquesFaris E. Mohammed, Nadia Smaoui Zghal, Dalinda Ben Aissa, Mostafa Mahmoud El-GayarAccording to the World Health Organization (WHO), breast cancer is a disease that leads to death, especially for women who have neglected or ignored the risk factors. Doctors can classify patients according to clinical information, famous disease symptoms, or similar cases. But, some cases are difficult to detect early or diagnose accurately. Therefore, the most important challenge faced by researchers … …Journal of Computer Science, Vol. 18, Issue 4 · 12 May 2022 · 6,526 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEvaluation of Classification Models for Predicting Mortality Rate Using Thyroid Cancer DataNorah Saleh AlghamdiMachine Learning (ML) can potentially enhance predictions in real-life domains. This study presents an evaluation and comparison of different ML methods which can be applied on thyroid cancer dataset, called Prostate, Lung, Colorectal and Ovarian (PLCO), of approximately 155,000 participants with thyroid cancer occurrence and mortality incidence. The ML models are explored for predicting mortality rates of patients with thyroid … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 7,788 accessesView PDFCite
Review ArticleOpen accessAll words, across the recordVisualization of Data Mining Techniques for the Prediction of Breast Cancer with High Accuracy RatesVasudev Sharma, Raj Kumar Rajasekaran, Shreya BadhrinarayananBreast cancer is one of the leading causes of death in women worldwide. Around one in 30 women are affected by breast cancer. Mammography has helped in detecting breast cancer in the early stages which have reduced mortality. The diagnosis of breast cancer is dependent on a variety of parameters. In this paper, we aim to create the best model … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 8,948 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA 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 accessAll words, across the recordFuzzy Modeling for Multi-Label Text Classification Supported by Classification AlgorithmsBeatriz Wilges, Gustavo Mateus, Silvia Nassar et al.The ever-increasing amount of information on the Web is organized in structured, semi-structured and unstructured data. Text classification systems, capable of handling such different structures, may facilitate the work of important tasks such as indexation and information retrieval in search engines. The objective of this research is to develop a method for the classification of documents into multiple categories with … …Journal of Computer Science, Vol. 12, Issue 7 · 22 Aug 2016 · 7,215 accessesView PDFCite