The study of clustering and classification of uncertain data addresses the challenges posed by imprecise, noisy, or inherently probabilistic measurements common in many modern data acquisition systems ...

Data that resides in a fixed field within a record or file is called structured data and have a defined schema. Unstructured data refers to information that either does not have a pre-defined data ...

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 ...

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.

Predictive analytics enables you to develop mathematical models to help you better understand the variables driving success. Predictive analytics relies on formulas that compare past successes and ...

*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 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 ...

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 ...