1. |
![문서 문서](/home/images/search/ico_pdf.gif) |
2018’ Welcome to Multivariate Statistics(II)
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Course description/Practice time/Final Exam/Term project |
![URL](/home/images/search/btnUrl.gif) |
2. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 6. Discrimination and Classification Analysis(DCA)
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6.1 Introduction
6.2 DCA with two clusters |
![URL](/home/images/search/btnUrl.gif) |
3. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 6. Discrimination and Classification Analysis(DCA)
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6.2 DCA with two clusters |
![URL](/home/images/search/btnUrl.gif) |
4. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 6. Discrimination and Classification Analysis(DCA)
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6.3 DCA with two multivariate normal clusters |
![URL](/home/images/search/btnUrl.gif) |
5. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 6. Discrimination and Classification Analysis(DCA)
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6.4 DCA with several clusters |
![URL](/home/images/search/btnUrl.gif) |
6. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 6. Discrimination and Classification Analysis(DCA)
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6.5 DCA with several multivariate normal clusters |
![URL](/home/images/search/btnUrl.gif) |
7. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 6. Discrimination and Classification Analysis(DCA)
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6.6 Evaluating classification function |
![URL](/home/images/search/btnUrl.gif) |
8. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 6. Discrimination and Classification Analysis(DCA)
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6.11 R for DCA: Practice Time |
![URL](/home/images/search/btnUrl.gif) |
9. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 7. Multidimensional Scaling(MDS)
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7.1 Introduction |
![URL](/home/images/search/btnUrl.gif) |
10. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 7. Multidimensional Scaling(MDS)
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7.2 Metric MDS |
![URL](/home/images/search/btnUrl.gif) |
11. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 7. Multidimensional Scaling(MDS)
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7.3 Non-metric MDS
7.6 R for MDS: Practice Time |
![URL](/home/images/search/btnUrl.gif) |
12. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 8. Correspondence Analysis(CRA)
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8.1 Introduction |
![URL](/home/images/search/btnUrl.gif) |
13. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 8. Correspondence Analysis(CRA)
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8.2 Simple CRA
8.3 Independence and homogeneity in CRA |
![URL](/home/images/search/btnUrl.gif) |
14. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 8. Correspondence Analysis(CRA)
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8.4 Multiple CRA |
![URL](/home/images/search/btnUrl.gif) |
15. |
![문서 문서](/home/images/search/ico_pdf.gif) |
Lecture 8. Correspondence Analysis(CRA)
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8.5 MCRA of classification variables data
8.6 R for CRA: Practice Time |
![URL](/home/images/search/btnUrl.gif) |