LITERATURE AND STUDY MATERIALS - READING LIST
"Introduction to Data Mining", Tan Pang -Ning, Steinbach Michael, Kumar Vipin, 2010, ΤΖΙΟΛΑ, ISBN: 978-960-418-162-9
Semester:
6th
Course Type:
Elective Specialization courses (ΠΜ-E)
Track:
CS (Computer Science)
Code:
ΥΣ11
ECTS:
6
TEACHING HOURS per week
Theory:
3
Seminar:
1
Laboratory:
-
Specializations
Foundations of Computer Science (S1):
-
Data and Knowledge Management (S2):
B Βασικό
Software (S3):
-
Hardware and Architecture (S4):
-
Communications and Networking (S5):
-
Signal and Information Processing (S6):
-
Related Courses
Course Content
The course covers data mining techniques: Data, problems, applications. General data analysis and processing techniques. Data categorization algorithms (decision trees, statistical techniques). Data categorization algorithms for multidimensional data and time series. Data grouping techniques. Techniques for finding correlations in multidimensional data and in relational data. Applications of data mining techniques in internet search problems and in biomedical problems.
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