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51 results for “Decision Forest”
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Research ArticleOpen accessIn the abstractIntelligent Intrusion Detection System Using RF, SVM, and DT: A Comparison-Based KDD Data SetWalaa Hassan Elashmawi, Alaa Sheta, Ahmad Al-QeremThe rapid growth of technology has brought about many advantages, but has also made networks more susceptible to security threats. Intrusion Detection Systems (IDS) play a vital role in protecting computer networks against malicious activities. Given the dynamic and constantly evolving nature of cyber threats, these systems must continuously adapt to maintain their effectiveness. Machine Learning (ML) methods have gained … …Journal of Computer Science, Vol. 21, Issue 8 · 28 Aug 2025 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelliHealth: A Machine Learning Driven Disease Detectionand Diet recommendation SystemAnkita Wadhwan, Priyanka Chawla, Sandeep Kaur, Usha MittalPeople all around the world are afflicted with various ailments. An accurate diagnosis can lower the risk of significant health problems developing, but an inaccurate diagnosis could have adverse implications. In this study, an ensemble-based strategy "IntelliHealth" has been presented to identify disorders of the thyroid, liver, and breast cancer using three machine learning (ML) approaches consisting of Support Vector … …Journal of Computer Science, Vol. 21, Issue 6 · 28 May 2025 · 5,239 accessesView PDFCite
Research ArticleOpen accessIn the abstractGradient Boosting for Heart Stroke Prediction: Investigating Unexpected Risk FactorsAniket Kailas Shahade, Priyanka V. DeshmukhHeart stroke prediction is a critical area in healthcare, aiming to identify individuals at risk and provide timely intervention. This research leverages machine learning algorithms, including Decision Tree, Random Forest, AdaBoost, and Gradient Boost, to predict the likelihood of stroke, with Gradient Boosting delivering the most accurate results. Our analysis uncovers intriguing and unexpected relationships between stroke risk and various … …Journal of Computer Science, Vol. 21, Issue 1 · 16 Dec 2024 · 4,943 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Analysis of Smote and CSSF Techniques for Diabetes Classification Using Imbalanced DataBashar Hamad Aubaidan, Rabiah Abdul Kadir, Mohamad Taha IjabDiabetes, a prevalent chronic metabolic disorder, poses a significant burden on healthcare systems worldwide. Accurate and timely diagnosis is crucial for effective management and complication prevention. Machine learning presents a promising solution but often faces challenges due to class imbalance within datasets, particularly the underrepresentation of diabetic cases. To address this issue, we introduce Cluster-based Synthetic Sample Filtering (CSSF), a … …Journal of Computer Science, Vol. 20, Issue 9 · 22 Jul 2024 · 5,005 accessesView PDFCite
Research ArticleOpen accessIn the abstractPhishing Website Detection Using Improved Multilayered Convolutional Neural NetworksHadia Bibi, Syed Rehan Shah, Mirza Murad Baig et al.The internet has become an essential part of many fields: Communication, entertainment, commerce, industrial production, agriculture, etc. Unfortunately, online users are vulnerable to various attacks; this could lead to financial damages and loss of personal information. Phishing is seen as an internet threat and a cybercrime where anyone can capture personal information and data by posing as a reliable source. … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,586 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Multi-Split Cross-Strategy for Enhancing Machine Learning Algorithms Prediction Results with Data Generated by Conditional Generative Adversarial NetworkAbdelfattah Abassi, Brahim Bakkas et al.In this study, we present a Multi-Split Cross-Strategy (MSC-Strategy) designed to leverage synthetic tabular data generated by a Conditional Generative Adversarial Network (CGAN). Our study aims to investigate the potential of synthetic data in comparison to real-world data for improving machine learning predictive results. Firstly, we develop a CGAN architecture tailored to generate synthetic tabular data, trained on a comprehensive … …Journal of Computer Science, Vol. 20, Issue 7 · 9 Apr 2024 · 6,701 accessesView PDFCite
Research ArticleOpen accessIn the abstractResearch on the Link Between Economic Development Variables and the Rate of Access to Drinking Water in Rural Senegal Using Machine LearningAnabilaye Moussa Coly, Alioune Ly, Ndolane Diouf et al.After pre-processing a set of data collected from Senegalese state structures, official United Nations (UN), and world bank sites and after replacing missing values by interpolation using the mean between two values, we study the effect of macroeconomic development variables on the rate of access to drinking water in rural Senegal. To do this, we use Machine Learning (ML) techniques … …American Journal of Applied Sciences, Vol. 20, Issue 1 · 20 Dec 2023 · 6,208 accessesView PDFCite
Research ArticleOpen accessIn the abstractHuman Age Predication from Face Images Based on Combining Deep Wavelet Network and Machine Learning AlgorithmsZahraa Salam Abu Ghrban, Nidhal K. EL AbbadiDue to the numerous variances in face appearance, age estimation using facial images is a difficult subject. Many factors can affect the estimation of human age such as race, face post, gender, lifestyle, etc. By considering more factors, the optimum performance may be obtained. In this study, we proposed a method to predict the age of facial images. The proposed … …Journal of Computer Science, Vol. 19, Issue 5 · 5 May 2023 · 5,573 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassifying and Predicting Students’ Performance using Improved Decision Tree C4.5 in Higher Education InstitutesMohammed Hikmat Sadiq, Nawzat Sadiq AhmedStudents’ information in higher education institutions increases yearly. It is hard for them to extract meaningful information from the huge amount of data manually. Such information can support academic staff to stop students from dropping out at the end of courses. This can be done by evaluating the students’ performance for the course and also by predicting their performance in … …Journal of Computer Science, Vol. 15, Issue 9 · 12 Sep 2019 · 9,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractBreast Cancer Grading using Machine Learning Approach AlgorithmsHiba Nabeel Zalloum, Saada Al Zeer, Amir Manassra et al.Recently, Breast Cancer (BC) becomes a more common cancer disease in women and it considers the most important sign which leads to death among women. Therefore, it requires efficient methods for detecting it to reduce the risk of death. A positive prognosis and greater chances of survival are improved if the BC is detected early. Currently, machine learning plays an … …Journal of Computer Science, Vol. 18, Issue 12 · 22 Dec 2022 · 6,619 accessesView PDFCite