This article provides a comprehensive review of data mining techniques and algorithms, including clustering, neural networks, and classification. It also highlights the issues related to the data mining process. Suitable for students and researchers in the field of data mining.

Intelligent Systems for Analytics Assignment 1 and 2 Presentation and Research Report

This assignment requires students to do a presentation on a recent academic paper related to Intelligent Systems for Analytics and write a research report on the same topic.

Learn about data mining techniques and algorithms, issues related to the process. Suitable for students and researchers.

Data Mining Techniques and Algorithms: A Review | Desklib

Data Mining Techniques and Algorithms: A Review

Introduction to Data Mining

University of Southeastern Philippines

Artificial Intelligence

DATA MINING. I. NTRODUCTION. The concept of data mining

Presentation

Marketing

The assignment delves into the application of the Apriori algorithm for association rule mining in business intelligence. It highlights the efficiency of this algorithm in process mining and evaluation, showcasing its significance in extracting valuable insights from data. The survey explores how association rules contribute to data intelligence and fact-finding techniques employed by various businesses.

Nanyang Technological University

Data Science and Big Data

Association Rule Mining for Business Intelligence

Statistics and Probability

Data Mining - Practical Machine Learning Tools and Techniques

Marketing Principles

Hartpury University and Hartpury College

Data Mining Techniques With Intelligent Systems

This presentation provides an overview of data mining, including the tools and techniques used. It explores the potential uses of data mining, such as market segmentation, customer churn prediction, fraud detection, direct marketing, and interactive marketing. The presentation also discusses the importance of data sources and provides examples of popular data mining tools like RapidMiner, Orange, Weka, KNIME, and KEEL.

Data Mining: Tools, Techniques, and Uses

PowerPoint Presentation

The assignment content discusses various data mining techniques such as classification analysis, association rule learning, outlier detection or anomaly, clustering analysis, regression analysis, tracking patterns, prediction technique, and their importance in different industries like communications, insurance, education, manufacturing, banking, retail, service providers, E-Commerce, supermarkets, Crime Investigation, and bioinformatics. These data mining techniques help organizations to acquire knowledge-based information, make profitable adjustments, automate forecasting of behavior and trends, and discover latent patterns.

Data Mining Techniques and Algorithms: A Review

End of preview

DATA MINING. I. NTRODUCTION. The concept of data mining

Association Rule Mining for Business Intelligence

Data Mining - Practical Machine Learning Tools and Techniques

Data Mining Techniques With Intelligent Systems

Data Mining: Tools, Techniques, and Uses

Unlocking Business Insights: Strategic Applications of Data Mining Techniques

Data Mining Techniques and Algorithms: A Review

End of preview

DATA MINING. I. NTRODUCTION. The concept of data mininglg...

Association Rule Mining for Business Intelligencelg...

Data Mining - Practical Machine Learning Tools and Techniqueslg...

Data Mining Techniques With Intelligent Systemslg...

Data Mining: Tools, Techniques, and Useslg...

Unlocking Business Insights: Strategic Applications of Data Mining Techniqueslg...

DATA MINING. I. NTRODUCTION. The concept of data mining

Association Rule Mining for Business Intelligence

Data Mining - Practical Machine Learning Tools and Techniques

Data Mining Techniques With Intelligent Systems

Data Mining: Tools, Techniques, and Uses

Unlocking Business Insights: Strategic Applications of Data Mining Techniques