|Website:||website containing additional information|
|Credits:||7.5 ECTS (=5.25 old credit points)|
|Period:||periode 4 (week 17 t/m 27, dwz 25-4-2005 t/m 8-7-2005; herkansing week 35)|
|Participants:||up till now 12 subscriptions|
|Schedule:||Dit is een oud rooster!
|Literature:||Lecture Notes "Advanced Data Mining".|
|Course form:||Lectures and Computer Lab.|
|Exam form:||Written exam and practical assignment.|
|Minimum effort to qualify for 2nd chance exam:||Om aan de aanvullende toets te mogen meedoen is ontbreken van ten hoogte 1 toetsactiviteit toegestaan.|
|Description:||The amount of data that is produced and stored by organisations is still
growing almost every day.|
This data needs to be processed and analysed to turn it into information and knowledge.
Knowledge thus obtained can improve our understanding and support decision making.
Some problems that data mining can help to solve:
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