Master of Science in European Economy and Business Law

BUSINESS STATISTICS

» 4 Appendix: Principal components analysis
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» 4. Model selection and evaluation
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» 5. Classification
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» 6. Regression and smoothing splines
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» 7. Local Polynomial Regression and Kernel Smoothing
data inserimento: 2015-10-21 08:42:53

» 8. Additive Models and Trees, Bagging and Boosting
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» 1. Introduction
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» 2. Tools for data analysis
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» 3. Linear regression
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» Textbook
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» AAPOR Report on Big Data
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» Top 10 data mining algorithms
data inserimento: 2018-09-18 14:20:24

» Revision week 1
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» Revision week 2
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» Revision week 2 Solutions
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» Revision week 3
data inserimento: 2019-10-02 08:03:58

» Revision week 4
data inserimento: 2019-10-08 17:53:42

» Revision week 5
data inserimento: 2019-10-16 15:24:12

» Glmnet tutorial video by Trevor Hastie
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» R studio - Links
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» Tutorial 1 - Linear regression
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» Tutorial 2 Model evaluation and selection
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» Tutorial 3: Logistic Regression
data inserimento: 2017-10-11 09:01:56

» Tutorial 4 - Regression and smoothing splines
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» Tutorial 5: local polynomial regression and kernel smoothing
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» Tutorial 6: additive models and trees
data inserimento: 2015-10-29 08:54:29

» Assignment 1
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» Assignment 2
data inserimento: 2019-10-01 08:17:18

» Assignment 3
data inserimento: 2019-10-09 12:59:27

» Assignment 4
data inserimento: 2019-10-18 14:51:29

» Assignment 5
data inserimento: 2019-11-04 16:46:55