TGGS > ECE > 512
Principles of Data Mining
Principles and algorithms of data mining. Data cleaning and integration. Descriptive and predictive mining. Frequent, sequential and structured pattern mining. Clustering. Outlier analysis and fraud detection. Other research topics in data mining.
Instructor(s) : Y. Chodpathumwan
Credits : (3-0-6)
Course Learning Outcome (What are they?)
| ELO1 | ELO2 | ELO3 | ELO4 | ELO5 | ELO6 | ELO7 | ELO8 | ELO9 | ELO10 |
| Morale and Ethics | Knowledge | Intellectual Skill | Interpersonal Skill and responsibility | Analytical, communications and IT skills | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 1 | 2 | 3 | 4 | 1 | 2 | 3 | 4 | 5 | 1 | 2 | 3 | 4 | 5 | 1 | 2 | 3 | 4 | 5 | 6 |
Revision : July 2020
Other Revisions : July 2021