Information Package / Course Catalogue
| Course Code | : MTK571 |
| Course Type | : Area Elective |
| Couse Group | : Second Cycle (Master's Degree) |
| Education Language | : Turkish |
| Work Placement | : N/A |
| Theory | : 3 |
| Prt. | : 0 |
| Credit | : 3 |
| Lab | : 0 |
| ECTS | : 8 |
Today, a lot of information can be collected via computer based technologies. Interpreting, evaluating the collected information is very important subject for decision systems. Data mining is useful field for many areas. The fundamentals of data mining will be mentioned in this course. Data mining methods are going to be explained in detail and some applications are going to be developed with these methods.
Data Warehouse. Introduction to Data Mining. Classification with Decision Trees. Classification and Regression Trees (CART). Memory Based Classification: K- Nearest Neighbor Algorithm. Clustering. Association Rules. Statistical Classification Models: Bayes Classification and Bayes Networks. Optimization Based Classification Models: Support Vector Machine.
| Lec. Rıfat AŞLIYAN |
| 1. | To be able to recognize the concepts of data warehouse and data mining. |
| 2. | To be able to acquire and use data mining methods. |
| 3. | To be able to develop the applications using data mining methods. |
| 4. | To be able to gain the skill of interpreting some interrelations among these concepts |
| 5. | To be able to use concepts in solving certain types of problems |
| 1. | Dr. Yalçın Özkan, Veri Madenciliği Yöntemleri (Methods of Data Mining), Papatya Yayıncılık,2008. |
| 2. | J.Han and M.Kamber, Data Mining Concept and Techniques, Morgan Kaufmann Publisher, 2006. |
| 3. | D.Pyle , Data Preparation for Data Mining, Dartmouth Publishing, Inc., 1999. |
| Type of Assessment | Count | Percent |
|---|---|---|
| Midterm Examination | 1 | %30 |
| Final Examination | 1 | %70 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 0 | 3 | 42 |
| Individual Work | 14 | 0 | 4 | 56 |
| Midterm Examination | 1 | 42 | 3 | 45 |
| Final Examination | 1 | 54 | 3 | 57 |
| TOTAL WORKLOAD (hours) | 200 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | PÇ-8 | PÇ-9 | PÇ-10 | PÇ-11 | PÇ-12 | PÇ-13 | PÇ-14 | PÇ-15 | |
OÇ-1 | 4 | 5 | 3 | 5 | 3 | 4 | 4 | ||||||||
OÇ-2 | 4 | 5 | 5 | 5 | 3 | 4 | 5 | ||||||||
OÇ-3 | 4 | 5 | 5 | 5 | 4 | 4 | 5 | ||||||||
OÇ-4 | 4 | 5 | 5 | 5 | 4 | 4 | 4 | ||||||||
OÇ-5 | 4 | 5 | 5 | 5 | 4 | 4 | 4 | ||||||||