42 results for “Supervised Algorithm”

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Research ArticleOpen accessEvery word in the titleSummarizing Relational Data Using Semi-Supervised Genetic Algorithm-Based Clustering TechniquesRayner AlfredProblem statement: In solving a classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets stored in multiple tables into a single table. Unfortunately, we may loss some information when we join tables with a high degree of one-to-many association. Therefore, data transformation becomes a tedious trial-and-error work and … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,585 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleAssessing Supervised Classification Algorithms for Mangrove Detection and Differentiation from Other Forest Types in Paiton District, Probolinggo RegencyKaruniawan Puji Wicaksono, Fathor Rohman, Yasushi MitsudaRemote sensing provides an effective approach for monitoring forest cover dynamics, yet distinguishing mangroves from other forest types remains challenging in heterogeneous coastal landscapes. This study compares six supervised classification algorithms: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Mixture Discriminant Analysis (MDA), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) for mangrove detection in Paiton, … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 1 Sep 2026 · 844 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleComparative Performance of Supervised Learning Algorithms for Flood Prediction in Kemaman, TerengganuNur Najihah Shaaban, Norlida Hassan, Aida Mustapha, Salama A. MostafaFlood is one of the most destructive phenomena all over the world. Because the flooding uncertainties and the urgency to prepare for disaster management, three specific technique approaches are compared in this study to predict the flood occurrence based on historical rainfall data. The study involved the rainfall data in Kemaman, Terengganu between 2017 and 2018 extracted from the official … …Journal of Computer Science, Vol. 17, Issue 5 · 7 May 2021 · 6,887 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsBin Bay: An Optimized Smart Waste Disposal System for a Sustainable Urban Life using LSTM and Fog ComputingShiny Duela, Dioline Sara, PrabavathiTo create green and smart cities, a smart and planned WasteManagement System (WMS) is a vital requirement. With the increase in the urbanpopulation and service delivery difficulties, smart cities are integratingtechnologies such as smart waste bins and Radio Frequency Identification (RFID)tags into their day-to-day operations to make solid waste management andcontrol more effective. Fog computing in waste management is becoming … …Journal of Computer Science, Vol. 18, Issue 11 · 16 Nov 2022 · 6,661 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsEvaluation 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 PDF Cite

Research ArticleOpen accessIn the keywordsDiscretization Numerical Data for Relational Data with One-to-Many RelationsRayner AlfredProblem statement: Handling numerical data stored in a relational database has been performed differently from handling those numerical data stored in a single table due to the multiple occurrences (one-to-many association) of an individual record in the non-target table and non-determinate relations between tables. Numbers in Multi-Relational Data Mining (MRDM) were often discretized, after considering the schema of the relational … …Journal of Computer Science, Vol. 5, Issue 7 · 31 Jul 2009 · 7,030 accessesView PDF Cite

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 PDF Cite

Research ArticleOpen accessIn the abstractA Misuse and Anomaly Intrusion Detection System Using Hybrid Supervised and Unsupervised Data Mining ApproachesHoma Molavi, Mohammad KhanbabaeiIntrusion Detection Systems (IDSs) play a crucial role in monitoring computer network security. Data mining and machine learning techniques facilitate the identification of intrusion patterns within large volumes of data. Hybrid data mining models have become increasingly popular in IDSs due to their enhanced effectiveness. This study presents a novel hybrid IDS that combines misuse and anomaly detection by integrating … …Journal of Computer Science, Vol. 22, Issue 6 · 6 Jul 2026 · 999 accessesView PDF Cite

Research ArticleOpen accessIn the abstractTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,427 accessesView PDF Cite

Research ArticleOpen accessIn the abstractOptimized Feature Selection Approach for Semi-Supervised Sentiment Analysis of E-Commerce FeedbackAlok Kumar Jena, Kakita Murali Gopal et al.In this globalized world, people prefer to buy products online without any hesitation. Usually, to acquire the quality of the product or brand, they examine the product’s reviews, which is a tedious job to do manually. The wide use of social media also encourages the users, to keep their views on the product in a global platform. By using machine … …Journal of Computer Science, Vol. 21, Issue 2 · 16 Jan 2025 · 6,179 accessesView PDF Cite