Clustering is a commonly considered data mining problem in the text domains. The problem finds numerous applications in customer segmentation, classification, collaborative filtering, visualization, ...

Entropy Minimization is a new clustering algorithm that works with both categorical and numeric data, and scales well to extremely large data sets. Data clustering is the process of placing data items ...

Data clustering, or cluster analysis, is the process of grouping data items so that similar items belong to the same group/cluster. There are many clustering techniques. In this article I'll explain ...

This course Introduces basic data mining concepts and techniques for discovering interesting patterns hidden in large-scale data sets, focusing on issues relating to effectiveness and efficiency.

Anomaly detection can be used to determine when something is noticeably different from the regular pattern. BYU professor Christophe Giraud-Carrier, director of the BYU Data Mining Lab, gave the ...

Think of data mining as digging for digital gold. It’s the technique of studying big data to reveal insights, trends, and links that aren't instantly apparent. In simple terms, it takes unprocessed ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.