CS 456 - Data Mining (Put on reserve 9/16/15.)

Description:
Introducing concepts, models, algorithms, and tools for solving data mining tasks; decision trees, time series, Bayesian methods, k-nearest neighbors, and relational databases. CS 456 and CS 556 are layered courses; students may not receive credit for both. Put on reserve 9/16/15. Will go inactive 8/24/18.

Prerequisites:
Prerequisites: CS 420 and either MATH 311 or BUS 221.

Credits: (4)

Learner Outcomes:
Upon successful completion of this course, the student will be able to:

Characterize specific data mining tasks.
Use machine learning algorithms to solve data clustering problems.
Identify the important of data mining in financial applications.

Learner Outcomes Approval Date:
11/24/10