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 ...

Incomplete data affects classification accuracy and hinders effective data mining. The following techniques are effective for working with incomplete data. The ISOM-DH model handles incomplete data ...

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 ...

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.

The updated 5th edition of the book Data Mining for Business Analytics from Galit Shmueli and collaborators and published by Wiley is a standard guide to data mining and analytics that adds two new co ...

*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.

This article, an excerpt from Java Data Mining: Strategy, Standard, and Practice by Mark F. Hornick, Erik Marcade, Sunil Venkayala (Morgan Kaufman, 2007), introduces data mining concepts for those new ...

It is expected that students seeking enrollment in this program will have sufficient foundational skills and aptitude in computer programming, statistical analysis, information systems, and databases.