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50 articles for “Decision Tree Learning”

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Research ArticleOpen accessEvery word in the titleRisk Prediction with Regression in Global Software Development using Machine Learning Approach: A Comparison of Linear and Decision Tree RegressionAsim Iftikhar, Shahrulniza Musa, Muhammad Alam et al.Software development through teams at different geographical locations is a trend of modern era, which is not only producing good results without costing lot of money, but also productive in relation to its cost with low risk and high return. This shift of perception of working in a group rather than alone is getting stronger day by day and has … …Journal of Computer Science, Vol. 17, Issue 2 · 3 Mar 2021 · 7,366 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,939 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIntelligent Digital Signal Modulation Recognition using Machine LearningMudhafar Haji Mala Abd, Sadegh AminifarInrecent years, modulation type recognition has received a lot of attentionacross the board. There are several methods to detect modulation types, butthere are only a few effective methods to handle signals with a higher level ofnoise. This study introduces an approach to verify the ability of differentmachine learning algorithms to automatically manage noise in detecting digitalmodulations. This research examines two … …Journal of Computer Science, Vol. 18, Issue 10 · 26 Sep 2022 · 6,095 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBig Data in Educational Institutions using RapidMiner to Predict Learning EffectivenessEvaristus Didik Madyatmadja, David Jumpa Malem Sembiring, Sinek Mehuli Br Perangin Angin et al.Schools, universities, colleges and other educational institutions store a lot of data related to students and teachers as well as those related to education. You can analyze this data to gain insights that can improve the operational efficiency of your organization. Educational institution's needs based on student behavior, student exam results, each student's growth and changed educational regulations can be … …Journal of Computer Science, Vol. 17, Issue 4 · 29 Apr 2021 · 6,834 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSupervised Machine Learning Model-Based Approach for Performance Prediction of StudentsAbdul Razaque, Abrar M. AlajlanPredicting students’ performance is one of the crucial issue for learning contexts, since it helps to develop alternative recommendation systems for academically weak students. Thus, several methods and practices have been applied for educational improvement. However, most of the existing methods do not determine the performance of the students. In this study, we have studied the execution of six machine … …Journal of Computer Science, Vol. 16, Issue 8 · 28 Aug 2020 · 7,082 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSRBIR: Semantic Region Based Image Retrieval by Extracting the Dominant Region and Semantic LearningI. Felci Rajam, S. ValliProblem statement: The Semantic Region Based Image Retrieval (SRBIR) system that automatically segments the dominant foreground region, consisting of the semantic concept of the image, such as elephants, roses and does the semantic learning, is proposed. Approach: The system segments an image into different regions and finds the dominant foreground region in it, which is the semantic concept of that … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 7,026 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 keywordsCOMPARING THE PERFORMANCE OF SEMANTIC IMAGE RETRIEVAL USING SPARQL QUERY, DECISION TREE ALGORITHM AND LIREMagesh, ThangarajThe ontology based framework is developed for representing image domain. The textual features of images are extracted and annotated as the part of the ontology. The ontology is represented in Web Ontology Language (OWL) format which is based on Resource Description Framework (RDF) and Resource Description Framework Schema (RDFS). Internally, the RDF statements represent an RDF graph which provides the … …Journal of Computer Science, Vol. 9, Issue 8 · 8 Jul 2013 · 6,705 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Machine Learning Framework for Strategic Gameplay Optimization in Scrabble Using Reinforcement LearningMohd Kaleem, Kanta Prasad Sharma, Tapsi Nagpal et al.This paper explores and compare various artificial intelligence-based techniques used for playing classic board game Scrabble. As the world is evolving around finding quick and efficient techniques for the solution of each problem using Machine learning, gaming industry is also a flourishing industry and has grown 9.8% compared to previous year and has generated a revenue of 26.14 billion dollars … …Journal of Computer Science, Vol. 22, Issue 9 · 22 Sep 2026 · 666 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Fraud Detection Methods in Banking Using Machine Learning TechniquesYoussef Tounsi, Ennouri TaziFraud detection in banking requires algorithms that balance classification performance, computational efficiency, and regulatory interpretability, criteria that are rarely benchmarked together. We present a comprehensive evaluation of nine machine learning approaches (Logistic Regression, Decision Tree, Random Forest, SVM, SGD, XGBoost, CatBoost, LightGBM, and MLP) across three datasets differing in size, imbalance severity, and feature type (synthetic, real-world PCA-anonymized, and large-scale … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,341 accessesView PDFCite