Predictive analytics, pattern recognition, and classification problems are not new ... This article provides a quick explanation of the nine most common data-mining techniques used in predictive ...

Abstract: This paper presents a comparative evaluation of data mining techniques such as Random Forest (RF), Support Vector Machine (SVM), and Naïve Bayes Tree (NBTree) classifiers for classifying ...

This project is developed as part of the COME 448 Data Mining ... techniques and machine learning models. Given a dataset containing documents from multiple authors, students will analyze and compare ...

AMGWO, a new feature selection method inspired by grey wolves, uses adaptive strategies to enhance machine learning models.

Abstract: In view of the rapid development of process mining ... different data sources, then analyze and summarize the specific algorithm classification literature at home and abroad in chronological ...

The exercises provide the basis of tutorial seminar and laboratory work ... The module covers supervised and unsupervised learning techniques with a specific application to data mining. Lectures will ...

Budoen, A. , Zhang, M. and Jr., L. (2025) A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites. Open Access Library Journal, 12, 1-22. doi: ...

Although the term “data mining” wasn’t coined until the 1990s, data mining techniques were used long before that. As the quality and complexity of data increased, software applications were ...

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Line Art Tips and Techniques – Drawing Tutorial Posted: May 21, 2025 | Last updated: May 21, 2025 Welcome to Winged Canvas, your Online School of Illustration and Art Nerd Community! 🌟 We're ...

This TDWI Insight Accelerator considers the challenges that organizations are facing with diverse, distributed data types and explores techniques and approaches that can help data engineers overcome ...