| Course title | |||||
| 情報工学特別講義(データマイニング) [Dedicated Lecture on Information Engineering] | |||||
| Course category | technology speciality courses,ets. | Requirement | Credit | 2 | |
| Department | Year | 3~4 | Semester | Fall | |
| Course type | Fall | Course code | 025811 | ||
| Instructor(s) | |||||
| 藤本 浩司, 柴原 一友, 藤田 桂英, 宮武 孝尚 [FUJIMOTO Kohji, SHIBAHARA Kazutomo, FUJITA Katsuhide, MIYATAKE Takahisa] | |||||
| Facility affiliation | Graduate School of Engineering | Office | Email address | ||
| Course description |
| Learning concept and basic skill of data mining, which extracts knowledge from big data |
| Expected Learning |
| Learning concept and basic skill in extraction knowledge from big data |
| Course schedule |
|
Day 1 Data mining and cunsumption society, How to predict the future by using possibility, Basic operation of R (statistical analysis software), Report Day 2 What is classification tree?, How to evaluate classification trees, Linear regression, Logistic regression, Non-parametric regression Day 3 Neural network, Support vector machine, Probabilistic-structured model (Bayes' theorem), Report |
| Prerequisites |
| N/A |
| Required Text(s) and Materials |
| Handout and Moodle |
| References |
| Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management |
| Assessment/Grading |
| Evaluate by attendance(50%) and assignments(50%) |
| Message from instructor(s) |
| Course keywords |
| Classification tree, Linear regression, Logistic regression, Non-parametric regression Neural network, Support vector machine, Bayes' theorem, R (statistical analysis software) |
| Office hours |
| Remarks 1 |
| Remarks 2 |
| Related URL |
| Lecture Language |
| Language Subject |
| Last update |
| 9/18/2018 4:09:36 PM |