Description of Individual Course Units
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Offered By |
Graduate School of Natural and Applied Sciences |
Level of Course Unit |
Second Cycle Programmes (Master's Degree) |
Course Coordinator |
PROFESSOR DOCTOR EFENDI NASIBOĞLU |
Offered to |
Ph.D. in Computer Science (English) |
Course Objective |
This course aims to provide the students with an overview of the fuzzy clustering and fuzzy classification problems. It also aims to handle the key computational techniques of prototype based and neighborhood based fuzzy clustering and classification models. |
Learning Outcomes of the Course Unit |
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Mode of Delivery |
Face -to- Face |
Prerequisites and Co-requisites |
None |
Recomended Optional Programme Components |
None |
Course Contents |
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Recomended or Required Reading |
Textbook(s): Höppner F., Klawonn F., Kruse R., Runkler T., Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition, Wiley, 1999. |
Planned Learning Activities and Teaching Methods |
The course is taught in a lecture, class presentation and discussion format. Besides the taught lecture, group presentations are to be prepared by the groups assigned and presented in a discussion session. In some weeks of the course, results of the homework given previously are discussed. |
Assessment Methods |
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Further Notes About Assessment Methods |
None |
Assessment Criteria |
To be announced. |
Language of Instruction |
English |
Course Policies and Rules |
To be announced. |
Contact Details for the Lecturer(s) |
To be announced. |
Office Hours |
To be announced. |
Work Placement(s) |
None |
Workload Calculation |
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Contribution of Learning Outcomes to Programme Outcomes |
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