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114 articles for “Decision Tree”
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Research ArticleOpen accessIn the keywordsA Comparative Study of Machine Learning Algorithms for Skin Cancer DetectionVineeth Victor, Amit Kumr Tyagi, Khushboo Tripathi et al.The skin is the largest organ in the human body, covering an area of around 20 square feet. Our skin keeps us safe from germs and the environment, helps us regulate our body temperature, and gives us the ability to feel touch, heat, and cold. More than 95 percent of all skin cancers are caused by ultraviolet (UV) radiation. UV … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 1,859 accessesView PDFCite
Research ArticleOpen accessIn the keywordsClassify 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 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 keywordsAdvising Approach to Enhance Students' Performance Level in Higher Education EnvironmentsAya M. Mostafa, Ayman E. Khedr, A. AbdoIntended Learning Outcomes (ILOs) is a major new approach to enhance students' performance level at any higher education institution. Moreover, it supports decision making based on the extracted information. It works as a framework for continuous improvement and evaluation in higher education environments. This study intends to achieve many benefits including; minimize wastages education through selecting the appropriate decision for … …Journal of Computer Science, Vol. 13, Issue 5 · 24 May 2017 · 7,448 accessesView PDFCite
Research ArticleOpen accessIn the keywordsToward a Good Decision to Improve the Weight of Control of Expenditure for Local CommunitiesAanouar Riad Solh, Mourad El BelkacemiIn order to improve the weight control of local government spending, we have developed a technique to supervise the classification of local authorities according to their expense ratios. This aims to develop the repository of rules and decision-making skills of business leaders of local communities and enabling to detect frauds in expenditure ratios that cause weakness of the Current Flow … …American Journal of Applied Sciences, Vol. 13, Issue 3 · 26 Mar 2016 · 6,992 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBenchmarking in the Academic Departments using Data Envelopment AnalysisMohammad Mahallati Rayeni, Faranak Hosseinzadeh SaljooghiProblem statement: The purpose of this study is to analyze efficiency and benchmarking using Data Envelopment Analysis (DEA) in departments of University. Benchmarking is a process of defining valid measures of performance comparison among peer decision making units (DMUs), using them to determine the relative positions of the peer DMUs and, ultimately, establishing a standard of excellence. Approach: DEA can … …American Journal of Applied Sciences, Vol. 7, Issue 11 · 8 Nov 2010 · 7,172 accessesView PDFCite
Research ArticleOpen accessIn the keywordsData Mining: A Preprocessing EngineLuai A. Shalabi, Zyad Shaaban, Basel KasasbehThis study is emphasized on different types of normalization. Each of which was tested against the ID3 methodology using the HSV data set. Number of leaf nodes, accuracy and tree growing time are three factors that were taken into account. Comparisons between different learning methods were accomplished as they were applied to each normalization method. A new matrix was designed … …Journal of Computer Science, Vol. 2, Issue 9 · 30 Sep 2006 · 34,390 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFuzzy 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
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
Research ArticleOpen accessIn the keywordsA Novel Ensemble Method for Regression via Classification ProblemsSami M. Halawani, Ibrahim A. Albidewi, Amir AhmadProblem statement: Regression via Classification (RvC) is a method in which a regression problem is converted into a classification problem. A discretization process is used to covert continuous target value to classes. The discretized data can be used with classifiers as a classification problem. Approach: In this study, we use a discretization method, Extreme Randomized Discretization (ERD), in which bin … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 7,383 accessesView PDFCite