筑波大学教育課程編成支援システム(EN)

01CF109 Data Mining

2.0 Credits, 1, 2 Year, FallAB Tue5,6
Mika Sato-Ilic

Course Overview

Data analysis techniques in data mining based on knowledge discovery from aspects of statistical learning and machine learning will be the main focus of discussion in this class.

Remarks

Identical to 0AL0301.
Online(Asynchronous)
Online(Synchronous)

Course Type

lectures

Relation to Degree Program Competences

Course Objectives(Learning Outcomes)

Data analysis techniques in data mining based on knowledge discovery from aspects of statistical learning and machine learning will be the main focus of discussion in this class.
This course will be accomplished both through the understanding of advanced methodologies related with exploratory data analyses in the core area of data analysis based on mathematical arguments and substantial impact from the real world.

Course Keywords

machine learning, Soft Computing, Statistical Science

Class Schedule

1.	What is data mining
2.	Multidimensional theory
3.	Multidimensional theory and its applications
4.	Machine learning
5.	Machine learning and its applications
6.	Statistical learning
7.	Statistical learning and its applications
8.	Symbolic data analysis
9.	Symbolic data analysis and its applications
10.	Data fusion theory

Course Prerequisites

Grading Philosophy

The evaluation will be based on the examination (20%) and reports (80%).

Course Hours Breakdown and Out-of-Class Learning

Fundamental knowledge and application of data mining

Textbooks, References,and Supplementary Materials

Materials will be distributed in class.

1. H.H. Bock and E. Diday (Eds.), Analysis of Symbolic Data, Springer, 2000
2. T. Hastie, R. Tibshirani, J.H. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer, 2001
3. M. Sato-Ilic and L.C. Jain, Innovations in Fuzzy Clustering, Springer, 2006
4. M. Kantardzic, Data Mining: Concepts, Models, Methods, and Algorithms, Wiley, 2011

Office Hours and Contact Information

Wednesday 11:00-12:00 1001766

Other(Behavioral expectations and points to note for students during coursework)

Fundamental knowledge in Mathematics

シラバス参照