データマイニング (130044) Data Mining (130044)
 
◇ 担当教員 Instructor : MD. ALTAF-UL-AMIN
◇ 単位数 Credits : 1単位 ◇ 選択・必修 Required/Elective : 選択 ◇ 講義室 Room : L1
◇ 講義スタイル Style : 講義/公開
◇ 開講時期 Quarter : Ⅲ期 木曜3限

◇ 授業目的 Course goals : Making students familiar with the theories of the data mining algorithms and introducing them to the relevant R based tools for practical use
◇ 授業内容 Course description : Multivariate Data and Concepts Of Variance, Metrics, Similarities and Distances
Basic Matrix and vector Algebra
Concept of Supervised and Unsupervised Learning
Principal Component Analysis
Hierarchical Clustering
K-Mean Clustering
Classification Trees
Expectation Maximization Algorithm
Naive Bayes Classifier
Partial Least Square Regression
Partial Least Square Discriminant Analysis
Support Vector Machines
Self Organizing Mapping
Introduction to Neural Networks
Introduction to Random Forest
Receiver Operating Characteristic (ROC) Curves
Statistical Tests and p-values

◇ 教科書 Textbook : No official/selected text book but students can read related books of their choice for better understanding
◇ 参考書 Reference materials : Lectures notes will be uploaded online for students
◇ 履修条件 Prerequisites : Basic knowledge of mathematics and statistices
◇ 成績評価 Grading : Grades will depend home works (25%), attendance(25%) and final examination (50%)

More than 50% classes must be attended
◇ オフィスアワー Office Hours : Almost always welcome for discussion---better make an appointment over e-mail (amin-m@is.naist.jp) before coming
◇ 配布資料 Handouts : 現在、配布資料はありません。