Data mining and pattern recognition form the cornerstone of modern data science by enabling the extraction of meaningful information from vast and complex data sets. These techniques integrate ...

Data mining is an analytical process designed to explore and analyze large data sets to discover meaningful patterns, correlations and insights. It involves using sophisticated data analysis tools to ...

The second step in data mining process is the application of various modeling techniques. These are used to calibrate the parameters to optimal values. Techniques employed largely depend on analytic ...

Temporal data mining involves the extraction of meaningful patterns and trends from time-stamped data sets across diverse sectors such as finance, healthcare, environmental sciences and the Internet ...

The exponentially increasing amounts of data being generated each year make getting useful information from that data more and more critical. The information frequently is stored in a data warehouse, ...

Researchers have given a boost to privacy and protection of proprietary or other sensitive information during data mining, while not compromising on the ability to discover useful patterns in huge ...

*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.

The visual data mining process, seen in the first part of this two-part article, revealed patterns in four dimensions between cumulative gas well production and independent variables. "Jump ...

Data mining is a buzz term that many people have heard in recent months or years. However, this tool for understanding the world that we live in remains underappreciated and generally misunderstood by ...

Data mining tools collect and analyze data much faster than humans. Learn what data mining is, how it works, and how to use it effectively. Data mining is an important big data management strategy ...