Course title
1M5210001
Clustering and Classification in Infocommunications Technology

 kanzawa yuuchi Click to show questionnaire result at 2019
Course content
Clustering and Classification are important tools in the era where we cannot structurize huge and complex data.
In this course,
their significance and outlines are provided.
Purpose of class
Students will learn the significance of clustering and classification technology in InfoCommunication field.
Students will learn some application examples of clustering and classification to InfoCommunication field.
Students will describe how clustering and classification are investigated now.
Goals and objectives
  1. Students can understand the significance of clustering and classification technology in InfoCommunication field.
  2. Students can describe some application examples of clustering and classification to InfoCommunication field.
  3. Students can describe how clustering and classification are investigated now.
Language
Japanese
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1． Introduction of this course Assignment 120minutes
2． Application examples of clustering and classification. Assignment 60minutes
3． Preprocessing datasets. Assignment 60minutes
4． Kmeans Assignment 60minutes
5． Fuzzy c-means. Assignment 60minutes
6． Fuzzy classification function and Adjust Rand index. Assignment 60minutes
7． How to make artificial datasets. Assignment 60minutes
8． Practice: applying kmeans to artificial datasets. Assignment 60minutes
9． Practice: applying kmeans to real datasets. Assignment 60minutes
10． Practice: applying fuzzy c-means to artificial datasets. Assignment 60minutes
11． Practice: applying fuzzy c-means to real datasets. Assignment 60minutes
12． Document clustering using spherical clustering methods　and Collaborative Filtering. Assignment 60minutes
13． Research trend for clustering and classification. Assignment 60minutes
14． Summary Assignment 60minutes
Total. - - 900minutes
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 Reports Total.
1. 33% 33%
2. 33% 33%
3. 34% 34%
Total. 100% -
Evaluation method and criteria
report
Textbooks and reference materials
recommended through class
Prerequisites
survey how clustering and classification are or could be applied to your own research field,
especially in your thesis.
Office hours and How to contact professors for questions
  • Wednesday 12:30-13:00
    The lecturer recommends making appointment in advance.
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
Active-learning course
More than one class is interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
N/A N/A
Education related SDGs:the Sustainable Development Goals
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
Last modified : Sun Mar 21 15:09:47 JST 2021