|Period:||period 1 (week 36 through 45, i.e., 5-9-2016 through 11-11-2016; retake week 1)|
|Participants:||up till now 0 subscriptions|
|Schedule:||Official schedule representation can be found in MyTimetable|
|Teachers:||Dit is een oud rooster!
|Contents:||Note: basic knowledge of probability, statistics and calculus is
Also, you should be able to write a program, but experience with the R language is not required.
The following subjects are discussed:
|Literature:||Lecture notes and selected articles.|
Lectures and Computer Lab.
|Exam form:||Written exam and practical assignments.|
|Minimum effort to qualify for 2nd chance exam:||Om aan de aanvullende toets te mogen meedoen moet de oorspronkelijke uitslag minstens 4 zijn.|
The amount of data that is produced and stored by companies and other organizations is still growing every day.
Examples of problems that data mining can help address are:
through the use of computers, computationally expensive data mining methods can be applied that were not even considered in the early days of statistical data analysis.
In this course we study a number of well-known data mining algorithms.
We discuss what type of problems they are suited for, their computational
complexity and how to interpret