資料採礦

Data Mining

學期

112-1

學分

3 學分

當期課號

537403

永久課號

MGEM30058

開課單位

工業工程與管理學系

授課教師

王志軒

校區

光復

類別

選修

上課時間表

節	週二
5 13:20–14:10	資料採礦 MB415 3 節連堂
6 14:20–15:10
7 15:30–16:20

* 根據陽明交大上課時間表所列

概述

Learning how to apply data-science skills to manufacturing and service sectors and following a PDCA loop (plan-do-check-action)

先修科目

Statistics (required), Programming (C/Python/R), Database (plus)

教學方式

R-language programming Open-source dataset

評分方式

1. Take-home assignments (4 times) 40% 2. Academic paper & project presentation 20% 3. Concept testing 40% (midterm & final exam)

課程大綱

Statistical computation & unsupervised learning
Machine learning & ensemble learning

週次計畫

週次	主題
第 1 週	Introduction to data science
第 2 週	Introduction to R programming
第 3 週	Data preprocessing
第 4 週	Statistical analysis
第 5 週	Hypothesis testing (Chi-square/Proportion test/T-test/ANOVA)
第 6 週	Unsupervised clustering (K-means, C-means, Gaussian mixture, hierarchical clustering, DBSCAN)
第 7 週	Association rule mining (apriori)
第 8 週	Basic classifiers (KNN, Naive Bayes, Logit regression)
第 9 週	Midterm research-proposal presentation
第 10 週	Midterm exam concept test
第 11 週	Decision tree (CART, C4.5, C5.0)
第 12 週	Ensemble learning (random forest, gradient boosting, adaboost)
第 13 週	Ensemble learning &amp ROC (receiver operating characteristics)
第 14 週	Advanced &amp biased regression (MARS, Ridge, Lasso)
第 15 週	Support vector machine (SVM)
第 16 週	Artificial neural network (ANN)
第 17 週	Final exam concept test
第 18 週	Final project presentation

教科書

Introduction to data mining, Pang-Ning Tan Data mining (concepts and techniques), Han & Kamber, Morgan Kaufman. Machine learning, Mitchell, McGraw-Hill. Applied data mining, Paolo Giudici, Wiley (全華代理) Data mining for business intelligence, Galit Shmueli et al., Wiley Data mining, Roiger & Geatz, Addison-Wesley (東華代理) Next generation of data mining applications, Kantardzic & Zurada, IEEE society. Pattern classification, Duda et al., Wiley-interscience. Educational training course materials (產學訓練自編教材)

Office Hours

地點: R411
時間: Wed. EF
聯絡方式: chihwang@mail.nctu.edu.tw