Data Mining and network analysis IDN0110 2016

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
• Classi�cation
• 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.