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ma8701:2017v:lecture_plan_and_progress [2017-04-19]
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ma8701:2017v:lecture_plan_and_progress [2017-04-19] (nåværende versjon)
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| | 5 | Rest of Ch. 3, except 3.7-3.8 | Linear methods for regression | [[http://www.math.ntnu.no/~bo/MA8701/2011v/pred.eng.medfigur.pdf|Multivariate prediction and regression]] | | | | 5 | Rest of Ch. 3, except 3.7-3.8 | Linear methods for regression | [[http://www.math.ntnu.no/~bo/MA8701/2011v/pred.eng.medfigur.pdf|Multivariate prediction and regression]] | | |
| | 6 | Ch. 4, except 4.4.3 and 4.5 | Linear methods for classification | [[http://www.math.ntnu.no/~bo/MA8701/2013v/SlidesWeek7-2013.pdf|Slides Ch. 4]] | | | | 6 | Ch. 4, except 4.4.3 and 4.5 | Linear methods for classification | [[http://www.math.ntnu.no/~bo/MA8701/2013v/SlidesWeek7-2013.pdf|Slides Ch. 4]] | | |
| | 7 | Ch. 5, except 5.8, 5.9 and Appendix | Basis expansions and regularization | [[http://www.math.ntnu.no/~bo/MA8701/2013v/SlidesWeek8-2013.pdf|Slides Ch. 5]] | | | | 7 | Ch. 5, except 5.7, 5.8, 5.9 and Appendix | Basis expansions and regularization | [[http://www.math.ntnu.no/~bo/MA8701/2013v/SlidesWeek8-2013.pdf|Slides Ch. 5]] | | |
| | 8 | Ch. 6 | Kernel smoothing methods | [[http://www.math.ntnu.no/~bo/MA8701/2011v/kernel-density-theory.pdf|Kernel density estimation]] | No lecture on Thursday 23 February. Trial exam. | | | 8 | Ch. 6, except 6.7 | Kernel smoothing methods | [[http://www.math.ntnu.no/~bo/MA8701/2011v/kernel-density-theory.pdf|Kernel density estimation]] | No lecture on Thursday 23 February. Trial exam. | |
| | 9 | Ch. 7 (7.7, 7.8, 7.9 and 7.12 are not in curriculum) | Model assessment and selection | [[http://www.math.ntnu.no/~bo/MA8701/2013v/chap7.pdf|Slides Ch. 7]] | | | | 9 | Ch. 7, except 7.7, 7.8, 7.9 and 7.12 | Model assessment and selection | [[http://www.math.ntnu.no/~bo/MA8701/2013v/chap7.pdf|Slides Ch. 7]] | | |
| | 10 | Ch. 7.10-7.11 and some remaining issues from 7.1-7.6. 8.1, 8.2, 8.7. | Model selection and inference | | | | | 10 | Ch. 7.10-7.11 and some remaining issues from 7.1-7.6. 8.1, 8.2, 8.7. | Model selection and inference | | | |
| | 11 | Ch. 9.1 (not all details), 9.2. //INTRODUCTION: Ch. 8.1, 8.2.1, 8.2.2// | Additive models, trees, and related methods (bagging, random forests) | [[https://folk.ntnu.no/bo/MA8701/2017v/bookchapter-Tree-structured-classifiers.pdf|Bookchapter (B. Ripley: Pattern Recognition and Neural Networks)]], \\ Example: [[https://folk.ntnu.no/bo/MA8701/2017v/CART1.pdf|Pruning and cross-validation]] | Additional reading: Ch. 3 in "Berk: Statistical Learning". | | | 11 | Ch. 9.1 (not all details), 9.2. //INTRODUCTION: Ch. 8.1, 8.2.1, 8.2.2// | Additive models, trees, and related methods (bagging, random forests) | [[https://folk.ntnu.no/bo/MA8701/2017v/bookchapter-Tree-structured-classifiers.pdf|Bookchapter (B. Ripley: Pattern Recognition and Neural Networks)]], \\ Example: [[https://folk.ntnu.no/bo/MA8701/2017v/CART1.pdf|Pruning and cross-validation]] | Additional reading: Ch. 3 in "Berk: Statistical Learning". | |