| BIL 4008 | Data Mining | 3+0+0 | 4 | ||||
| Year / Semester | Spring semester | ||||||
| Level of Course | First Cycle | ||||||
| Status | Elective | ||||||
| Department | Computer Engineering | ||||||
| Prerequisites and co-requisites | N/A | ||||||
| Mode of Delivery | Face to face | ||||||
| Contact hours | 14 weeks | ||||||
| Lecturer | Asst. Prof. Dr. Murat Aykut | ||||||
| Co-Lecturer | |||||||
| Language of instruction | Turkish | ||||||
| Internship | N/A | ||||||
| Course Syllabus | |||||||
| Week | Subject | Related Notes / Files | |||||
| Week 1 | Data Mining Concepts: Data Mining Process, Data Warehouses, Data Marts, Large Data Sets | ||||||
| Week 2 | Preparing the Data: Representation of Raw Data, Characteristics of Raw Data, Transformation of Raw Data | ||||||
| Week 3 | Missing Data, Time Dependent Data, Outlier Analysis | ||||||
| Week 4 | Data Reduction: Feature Reduction, Relief Algorithm, Entropy Measure for Ranking Features, PCA | ||||||
| Week 5 | Value Reduction, Feature Discretization: ChiMerge Technique, Case Reduction | ||||||
| Week 6 | Learning From Data: Support Vector Machines, k-NN, model selection vs generalization | ||||||
| Week 7 | Bayesian Classification, Logistic Regression, LDA | ||||||
| Week 8 | Decision Trees | ||||||
| Week 9 | Midterm exam | ||||||
| Week 10 | Ensemble Learning: Bagging, Boosting, AdaBoost | ||||||
| Week 11 | Cluster Analysis: DBSCAN, DENCLUE | ||||||
| Week 12 | Association Rules: Apriori, FP Growth | ||||||
| Week 13 | Web Mining, Text Mining | ||||||
| Week 14 | Graph Mining, Temporal Data Mining, Spatial Data Mining | ||||||
| Week 15 | Visualization Methods | ||||||
| Week 16 | Final exam | ||||||
| Textbook / Material | |||||||
| 1 | Data Mining - Concepts, Models, Methods, and Algorithms - Mehmed Kantardzic, 2nd edition, Wiley, 2011, 534 pages | ||||||
| Recommended Reading | |||||||
| 2 | Data Mining: Concepts and Techniques 3rd edition - Jiawei Han, Micheline Kamber, Jian Pei, Morgan Kaufmann, 2012, 744 pages. | ||||||
All announcements will be made, and resources will be shared via course Piazza page (join as a student to class "BIL 4008"). The access code will be given in the first course..