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課程名稱 |
探索式多變量資料分析
Exploratory Multivariate Data Analysis |
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開課學期 |
112-1 |
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授課對象 |
生物資源暨農學院 生物機電工程學系 |
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授課教師 |
周呈霙 |
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課號 |
BME7909 |
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課程識別碼 |
631 M3110 |
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班次 |
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學分 |
3.0 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期一7,8,9(14:20~17:20) |
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上課地點 |
知207 |
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備註 |
專業選修(人工智慧)
總人數上限：30人 |
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課程簡介影片 |
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核心能力關聯 |
本課程尚未建立核心能力關連 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
This course covers methods for analyzing multivariate data.
1. Graphical methods
2. Modeling and inference using the multivariate normal distribution
- Multivariate data and models
- Multivariate Normal distribution
- Traditional inference: Multivariate Regression, MANOVA, etc.
- Links with mixed linear models and hierarchical modeling.
3. Variable selection – LARS, LASSO
4. Exploratory techniques based on eigenvalue and singular decomposition
- SVD of a data matrix; special decomposition
- Principal Component Analysis
- Factor Analysis
- Canonical Correlation
5. Classification and clustering
- Linear discrimination
- Classification trees
- Hierarchical clustering
6. K-means clustering
- Dimension reduction
- Multidimensional scaling
7. Correspondence analysis |
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課程目標 |
To learn how to analyze data sets and summarize their main characteristics through visual methods or statistical models.
To explore what the data can tell us beyond the formal modeling or hypothesis testing tasks. |
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課程要求 |
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預期每週課後學習時數 |
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Office Hours |
另約時間 |
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指定閱讀 |
Rencher, METHODS OF MULTIVARIATE ANALYSIS 3/E 2012 |
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參考書目 |
Rencher, A. C., and Christensen W. “Methods of Multivariate Analysis”, Wiley, 3rd Edition, 2012.
Wolfgang Karl Härdle and Léopold Simar “Applied Multivariate Statistical Analysis” 5th Edition, 2019.
Husson, F., Le, S., and Pages, J. “Exploratory Multivariate Analysis by Example Using R”, CPC Press, 2nd Edition, 2017. |
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評量方式
(僅供參考) |
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No. |
項目 |
百分比 |
說明 |
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1. |
In-class participation and Homework |
20% |
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2. |
Project and presentation |
20% |
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3. |
Midterm Exam |
30% |
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4. |
Final Exam |
30% |
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針對學生困難提供學生調整方式 |
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上課形式 |
以錄影輔助 |
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作業繳交方式 |
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考試形式 |
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其他 |
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