Data Mining and network analysis IDN0110 2016
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Spring 2015/2016
IDN0110: Data Mining and network analysis
Taught by: Sven Nõmm
EAP: 6.0
Time and place:
Lectures: 17:15-18:45 TBA
17:45-19:15 TBA
Labs: 14:00-15:30 TBA
Consultation: by appointment TBA
Additional information: sven.nomm@ttu.ee
Overview
The course aims to provide knowledge of theory behind different methods of data mining. Is is spanned around four "super problems" of data mining:
- Clustering
- Classification
- Association pattern mining
- Outlier analysis
Main topics of the course:
- Data types and Data Preparation
- Similarity and Distances, Association Pattern Mining,
- Cluster Analysis, Classification, Outlier analysis
- Data streams, Text Data, Time Series, Discrete Sequences,
- Spatial Data, Graph Data, Web Data, Social Network Analysis
- Privacy-Preserving Data Mining
Evaluation
- 2x mandatory closed book tests. Each test gives 10% of the final grade.
- 4x mandatory home assignments (Computational assignment +short write up.) 30% of the final grade (computed on the basis of three best results)
- final exam (gives 50 % of the final grade): Written report on assigned topic + discussion with lecturer.
Exam prerequisites: both closed book tests are accepted (graded as 51 or higher), all 4 home assignments are accepted (graded as 51 or higher).
- 91 < score -- grade 5 (excellent)
- 81 < score < 90 -- grade 4 (very good)
- 71 < score < 80 -- grade 3 (good)
- 61 < score < 70 -- grade 2 (satisfactory)
- 51 < score < 60 -- grade 1 (pass)
score ≤ 50 -- a student has failed to pass
Lectures
Lecture slides, necessary files, links and other necessary information would appear here before the lecture or practice.