From a35facc6e5f3f393259dd2a45b6981f361c50d65 Mon Sep 17 00:00:00 2001 From: chriskolb <39267431+chriskolb@users.noreply.github.com> Date: Fri, 18 Oct 2024 11:30:09 +0200 Subject: [PATCH] remove chap 20 GP and re-add featsel as extra chapter --- .../20_gaussian_processes/20-01-bayes-lm.md | 16 ---------------- .../20_gaussian_processes/20-02-basic.md | 15 --------------- .../20_gaussian_processes/20-03-covariance.md | 15 --------------- .../20_gaussian_processes/20-04-prediction.md | 15 --------------- .../20_gaussian_processes/20-05-training.md | 15 --------------- content/chapters/20_gaussian_processes/_index.md | 4 ---- .../20-01-intro.md} | 4 ++-- .../20-02-perf-msr.md} | 4 ++-- .../20-03-cs-1.md} | 0 .../20-04-cs-2.md} | 0 .../20-05-cs-3.md} | 4 ++-- .../20-06-cc-1.md} | 4 ++-- .../20-07-cc-2.md} | 4 ++-- .../20-08-smpl-1.md} | 4 ++-- .../20-09-smpl-2.md} | 0 .../_index.md | 2 +- .../21-01-intro.md} | 4 ++-- .../21-02-losses.md} | 4 ++-- .../21-03-methods-1.md} | 4 ++-- .../21-04-methods-2.md} | 4 ++-- .../_index.md | 2 +- .../22-01-intro.md} | 4 ++-- .../22-02-simple.md} | 4 ++-- .../22-03-ftl.md} | 4 ++-- .../22-04-ftrl.md} | 4 ++-- .../22-05-ftl-oqo.md} | 4 ++-- .../22-06-oco-1.md} | 4 ++-- .../22-07-oco-2.md} | 4 ++-- .../_index.md | 2 +- .../30_feature_selection/30-01-introduction.md | 14 ++++++++++++++ .../30-02-motivating-examples.md | 15 +++++++++++++++ .../30_feature_selection/30-03-filters1.md | 15 +++++++++++++++ .../30_feature_selection/30-04-filters2.md | 15 +++++++++++++++ .../30_feature_selection/30-05-wrapper.md | 15 +++++++++++++++ content/chapters/30_feature_selection/_index.md | 5 +++++ 35 files changed, 116 insertions(+), 117 deletions(-) delete mode 100644 content/chapters/20_gaussian_processes/20-01-bayes-lm.md delete mode 100644 content/chapters/20_gaussian_processes/20-02-basic.md delete mode 100644 content/chapters/20_gaussian_processes/20-03-covariance.md delete mode 100644 content/chapters/20_gaussian_processes/20-04-prediction.md delete mode 100644 content/chapters/20_gaussian_processes/20-05-training.md delete mode 100644 content/chapters/20_gaussian_processes/_index.md rename content/chapters/{21_imbalanced_learning/21-01-intro.md => 20_imbalanced_learning/20-01-intro.md} (88%) rename content/chapters/{21_imbalanced_learning/21-02-perf-msr.md => 20_imbalanced_learning/20-02-perf-msr.md} (87%) rename content/chapters/{21_imbalanced_learning/21-03-cs-1.md => 20_imbalanced_learning/20-03-cs-1.md} (100%) rename content/chapters/{21_imbalanced_learning/21-04-cs-2.md => 20_imbalanced_learning/20-04-cs-2.md} (100%) rename content/chapters/{21_imbalanced_learning/21-05-cs-3.md => 20_imbalanced_learning/20-05-cs-3.md} (82%) rename content/chapters/{21_imbalanced_learning/21-06-cc-1.md => 20_imbalanced_learning/20-06-cc-1.md} (86%) rename content/chapters/{21_imbalanced_learning/21-07-cc-2.md => 20_imbalanced_learning/20-07-cc-2.md} (86%) rename 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content/chapters/{23_online_learning/23-02-simple.md => 22_online_learning/22-02-simple.md} (81%) rename content/chapters/{23_online_learning/23-03-ftl.md => 22_online_learning/22-03-ftl.md} (81%) rename content/chapters/{23_online_learning/23-04-ftrl.md => 22_online_learning/22-04-ftrl.md} (81%) rename content/chapters/{23_online_learning/23-05-ftl-oqo.md => 22_online_learning/22-05-ftl-oqo.md} (81%) rename content/chapters/{23_online_learning/23-06-oco-1.md => 22_online_learning/22-06-oco-1.md} (84%) rename content/chapters/{23_online_learning/23-07-oco-2.md => 22_online_learning/22-07-oco-2.md} (84%) rename content/chapters/{23_online_learning => 22_online_learning}/_index.md (56%) create mode 100644 content/chapters/30_feature_selection/30-01-introduction.md create mode 100644 content/chapters/30_feature_selection/30-02-motivating-examples.md create mode 100644 content/chapters/30_feature_selection/30-03-filters1.md create mode 100644 content/chapters/30_feature_selection/30-04-filters2.md create mode 100644 content/chapters/30_feature_selection/30-05-wrapper.md create mode 100644 content/chapters/30_feature_selection/_index.md diff --git a/content/chapters/20_gaussian_processes/20-01-bayes-lm.md b/content/chapters/20_gaussian_processes/20-01-bayes-lm.md deleted file mode 100644 index cd30685..0000000 --- a/content/chapters/20_gaussian_processes/20-01-bayes-lm.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -title: "Chapter 20.01: The Bayesian Linear Model" -weight: 20001 ---- -We begin by reviewing the Bayesian formulation of a linear model and show that instead of point estimates for parameters and predictions, we obtain an entire posterior and predictive distribution. - - - -### Lecture video - -{{< video id="H7Qy1X12Ypo" >}} - -### Lecture slides - -{{< pdfjs file="https://github.com/slds-lmu/lecture_advml/raw/main/slides-pdf/slides-gp-bayes-lm.pdf" >}} - diff --git a/content/chapters/20_gaussian_processes/20-02-basic.md b/content/chapters/20_gaussian_processes/20-02-basic.md deleted file mode 100644 index 2b8c531..0000000 --- a/content/chapters/20_gaussian_processes/20-02-basic.md +++ /dev/null @@ -1,15 +0,0 @@ ---- -title: "Chapter 20.02: Gaussian Processes" -weight: 20002 ---- -In this section, we introduce the basic idea behind Gaussian processes. We move from weight to function space and build some intuition on distributions over functions, discuss GPs' marginalization property, derive GP priors, and interpret GPs as indexed families. - - - -### Lecture video - -{{< video id="Uv54SlxflhQ" >}} - -### Lecture slides - -{{< pdfjs file="https://github.com/slds-lmu/lecture_advml/raw/main/slides-pdf/slides-gp-basic.pdf" >}} diff --git a/content/chapters/20_gaussian_processes/20-03-covariance.md b/content/chapters/20_gaussian_processes/20-03-covariance.md deleted file mode 100644 index 0908539..0000000 --- a/content/chapters/20_gaussian_processes/20-03-covariance.md +++ /dev/null @@ -1,15 +0,0 @@ ---- -title: "Chapter 20.03: Covariance Functions for GPs" -weight: 20003 ---- -In this section, we discuss the role of covariance functions in GPs and introduce the most common choices. - - - -### Lecture video - -{{< video id="8fB3RwxNObw" >}} - -### Lecture slides - -{{< pdfjs file="https://github.com/slds-lmu/lecture_advml/raw/main/slides-pdf/slides-gp-covariance.pdf" >}} diff --git a/content/chapters/20_gaussian_processes/20-04-prediction.md b/content/chapters/20_gaussian_processes/20-04-prediction.md deleted file mode 100644 index a4b461f..0000000 --- a/content/chapters/20_gaussian_processes/20-04-prediction.md +++ /dev/null @@ -1,15 +0,0 @@ ---- -title: "Chapter 20.04: Gaussian Process Prediction" -weight: 20004 ---- -In this section, we show how to derive the posterior process and discuss further properties of GPs as well as noisy GPs. - - - -### Lecture video - -{{< video id="qlfUlFaP94g" >}} - -### Lecture slides - -{{< pdfjs file="https://github.com/slds-lmu/lecture_advml/raw/main/slides-pdf/slides-gp-prediction.pdf" >}} diff --git a/content/chapters/20_gaussian_processes/20-05-training.md b/content/chapters/20_gaussian_processes/20-05-training.md deleted file mode 100644 index 9b6fe3d..0000000 --- a/content/chapters/20_gaussian_processes/20-05-training.md +++ /dev/null @@ -1,15 +0,0 @@ ---- -title: "Chapter 20.05: Gaussian Process Training" -weight: 20005 ---- -In this section, we show how Gaussian processes are actually trained using maximum likelihood estimation and exploiting the fact that we can learn covariance functions' hyperparameters on the fly. - - - -### Lecture video - -{{< video id="S0GqTy2gLf0" >}} - -### Lecture slides - -{{< pdfjs file="https://github.com/slds-lmu/lecture_advml/raw/main/slides-pdf/slides-gp-training.pdf" >}} diff --git a/content/chapters/20_gaussian_processes/_index.md b/content/chapters/20_gaussian_processes/_index.md deleted file mode 100644 index 14d3fd5..0000000 --- a/content/chapters/20_gaussian_processes/_index.md +++ /dev/null @@ -1,4 +0,0 @@ ---- -title: "Chapter 20: Gaussian Processes" ---- -This chapter introduces Gaussian processes as a model class. Gaussian processes are non-parametric approaches with ubiquitous application that model entire distributions in function space. \ No newline at end of file diff --git a/content/chapters/21_imbalanced_learning/21-01-intro.md b/content/chapters/20_imbalanced_learning/20-01-intro.md similarity index 88% rename from content/chapters/21_imbalanced_learning/21-01-intro.md rename to content/chapters/20_imbalanced_learning/20-01-intro.md index 8474f2c..a8f6379 100644 --- a/content/chapters/21_imbalanced_learning/21-01-intro.md +++ b/content/chapters/20_imbalanced_learning/20-01-intro.md @@ -1,6 +1,6 @@ --- -title: "Chapter 21.01: Introduction" -weight: 21001 +title: "Chapter 20.01: Introduction" +weight: 20001 --- We define the phenomenon of imbalanced data sets and explain its consequences on accuarcy. Furthermore, we introduce some techniques for handling imbalanced data sets. diff --git a/content/chapters/21_imbalanced_learning/21-02-perf-msr.md b/content/chapters/20_imbalanced_learning/20-02-perf-msr.md similarity index 87% rename from content/chapters/21_imbalanced_learning/21-02-perf-msr.md rename to content/chapters/20_imbalanced_learning/20-02-perf-msr.md index 6077aaf..219be06 100644 --- a/content/chapters/21_imbalanced_learning/21-02-perf-msr.md +++ b/content/chapters/20_imbalanced_learning/20-02-perf-msr.md @@ -1,6 +1,6 @@ --- -title: "Chapter 21.02: Performance Measures" -weight: 21002 +title: "Chapter 20.02: Performance Measures" +weight: 20002 --- We introduce performance measures other than accuracy and explain their advantages over accuracy for imbalanced date. In addition we introduce extensions of these measures for multiclass settings. diff --git a/content/chapters/21_imbalanced_learning/21-03-cs-1.md b/content/chapters/20_imbalanced_learning/20-03-cs-1.md similarity index 100% rename from content/chapters/21_imbalanced_learning/21-03-cs-1.md rename to content/chapters/20_imbalanced_learning/20-03-cs-1.md diff --git a/content/chapters/21_imbalanced_learning/21-04-cs-2.md b/content/chapters/20_imbalanced_learning/20-04-cs-2.md similarity index 100% rename from content/chapters/21_imbalanced_learning/21-04-cs-2.md rename to content/chapters/20_imbalanced_learning/20-04-cs-2.md diff --git a/content/chapters/21_imbalanced_learning/21-05-cs-3.md b/content/chapters/20_imbalanced_learning/20-05-cs-3.md similarity index 82% rename from content/chapters/21_imbalanced_learning/21-05-cs-3.md rename to content/chapters/20_imbalanced_learning/20-05-cs-3.md index 9660e2a..c6f51a3 100644 --- a/content/chapters/21_imbalanced_learning/21-05-cs-3.md +++ b/content/chapters/20_imbalanced_learning/20-05-cs-3.md @@ -1,6 +1,6 @@ --- -title: "Chapter 21.05: Cost-Sensitive Learning 3" -weight: 21005 +title: "Chapter 20.05: Cost-Sensitive Learning 3" +weight: 20005 --- We explain the concepts of instance specific costs and cost-sensitive OVO. diff --git a/content/chapters/21_imbalanced_learning/21-06-cc-1.md b/content/chapters/20_imbalanced_learning/20-06-cc-1.md similarity index 86% rename from content/chapters/21_imbalanced_learning/21-06-cc-1.md rename to content/chapters/20_imbalanced_learning/20-06-cc-1.md index 0dbbf56..e808b66 100644 --- a/content/chapters/21_imbalanced_learning/21-06-cc-1.md +++ b/content/chapters/20_imbalanced_learning/20-06-cc-1.md @@ -1,6 +1,6 @@ --- -title: "Chapter 21.06: Cost Curves 1" -weight: 21006 +title: "Chapter 20.06: Cost Curves 1" +weight: 20006 --- We introduce cost curves for misclassif error and explain the duality between ROC points and cost lines. diff --git a/content/chapters/21_imbalanced_learning/21-07-cc-2.md b/content/chapters/20_imbalanced_learning/20-07-cc-2.md similarity index 86% rename from content/chapters/21_imbalanced_learning/21-07-cc-2.md rename to content/chapters/20_imbalanced_learning/20-07-cc-2.md index a56a187..622d1d9 100644 --- a/content/chapters/21_imbalanced_learning/21-07-cc-2.md +++ b/content/chapters/20_imbalanced_learning/20-07-cc-2.md @@ -1,6 +1,6 @@ --- -title: "Chapter 21.07: Cost Curves 2" -weight: 21007 +title: "Chapter 20.07: Cost Curves 2" +weight: 20007 --- We explain cost curves with cost matrices and comparing classifiers. In addition we do a wrap-up comparision to ROC. diff --git a/content/chapters/21_imbalanced_learning/21-08-smpl-1.md b/content/chapters/20_imbalanced_learning/20-08-smpl-1.md similarity index 86% rename from content/chapters/21_imbalanced_learning/21-08-smpl-1.md rename to content/chapters/20_imbalanced_learning/20-08-smpl-1.md index 0c5ec40..48bb010 100644 --- a/content/chapters/21_imbalanced_learning/21-08-smpl-1.md +++ b/content/chapters/20_imbalanced_learning/20-08-smpl-1.md @@ -1,6 +1,6 @@ --- -title: "Chapter 21.08: Sampling Methods 1" -weight: 21008 +title: "Chapter 20.08: Sampling Methods 1" +weight: 20008 --- We introduce the idea of sampling methods for dealing with imbalanced data. In addition, we explain certain undersampling techniques. diff --git a/content/chapters/21_imbalanced_learning/21-09-smpl-2.md b/content/chapters/20_imbalanced_learning/20-09-smpl-2.md similarity index 100% rename from content/chapters/21_imbalanced_learning/21-09-smpl-2.md rename to content/chapters/20_imbalanced_learning/20-09-smpl-2.md diff --git a/content/chapters/21_imbalanced_learning/_index.md b/content/chapters/20_imbalanced_learning/_index.md similarity index 66% rename from content/chapters/21_imbalanced_learning/_index.md rename to content/chapters/20_imbalanced_learning/_index.md index fb6c75e..08e2d83 100644 --- a/content/chapters/21_imbalanced_learning/_index.md +++ b/content/chapters/20_imbalanced_learning/_index.md @@ -1,4 +1,4 @@ --- -title: "Chapter 21: Imbalanced Learning" +title: "Chapter 20: Imbalanced Learning" --- This chapter introduces techniques for learning on imbalanced datasets. diff --git a/content/chapters/22_multitarget_learning/22-01-intro.md b/content/chapters/21_multitarget_learning/21-01-intro.md similarity index 89% rename from content/chapters/22_multitarget_learning/22-01-intro.md rename to content/chapters/21_multitarget_learning/21-01-intro.md index 65e112e..325fd13 100644 --- a/content/chapters/22_multitarget_learning/22-01-intro.md +++ b/content/chapters/21_multitarget_learning/21-01-intro.md @@ -1,6 +1,6 @@ --- -title: "Chapter 22.01: Introduction" -weight: 22001 +title: "Chapter 21.01: Introduction" +weight: 21001 --- In this chapter we emphasize the practical relevance of multi-target prediction problems. In addition, we name some special cases of multi-target prediction and establish the differences between transductive and inductive learning problems. diff --git a/content/chapters/22_multitarget_learning/22-02-losses.md b/content/chapters/21_multitarget_learning/21-02-losses.md similarity index 89% rename from content/chapters/22_multitarget_learning/22-02-losses.md rename to content/chapters/21_multitarget_learning/21-02-losses.md index 5bb8de0..7676b0a 100644 --- a/content/chapters/22_multitarget_learning/22-02-losses.md +++ b/content/chapters/21_multitarget_learning/21-02-losses.md @@ -1,6 +1,6 @@ --- -title: "Chapter 22.02: Loss functions" -weight: 22002 +title: "Chapter 21.02: Loss functions" +weight: 21002 --- In this chapter we introduce loss functions for multi-target prediction problems, explain the differences between instance-wise and decomposable losses and introduce the risk minimizer for both the hamming and 0/1 subset losses. diff --git a/content/chapters/22_multitarget_learning/22-03-methods-1.md b/content/chapters/21_multitarget_learning/21-03-methods-1.md similarity index 81% rename from content/chapters/22_multitarget_learning/22-03-methods-1.md rename to content/chapters/21_multitarget_learning/21-03-methods-1.md index cde7bec..b0a3a77 100644 --- a/content/chapters/22_multitarget_learning/22-03-methods-1.md +++ b/content/chapters/21_multitarget_learning/21-03-methods-1.md @@ -1,6 +1,6 @@ --- -title: "Chapter 22.03: Methods for Multi-target Prediction 1" -weight: 22003 +title: "Chapter 21.03: Methods for Multi-target Prediction 1" +weight: 21003 --- In this chapter we introduce the concepts of independent models for targets, mean regularization, stacking and weight sharing in DL. diff --git a/content/chapters/22_multitarget_learning/22-04-methods-2.md b/content/chapters/21_multitarget_learning/21-04-methods-2.md similarity index 82% rename from content/chapters/22_multitarget_learning/22-04-methods-2.md rename to content/chapters/21_multitarget_learning/21-04-methods-2.md index e02a151..182f316 100644 --- a/content/chapters/22_multitarget_learning/22-04-methods-2.md +++ b/content/chapters/21_multitarget_learning/21-04-methods-2.md @@ -1,6 +1,6 @@ --- -title: "Chapter 22.04: Methods for Multi-target Prediction 2" -weight: 22004 +title: "Chapter 21.04: Methods for Multi-target Prediction 2" +weight: 21004 --- In this chapter we introduce the Kronecker kernel ridge regression, graph relations in targets, probabilistic classifier chains and low-rank approximations. diff --git a/content/chapters/22_multitarget_learning/_index.md b/content/chapters/21_multitarget_learning/_index.md similarity index 60% rename from content/chapters/22_multitarget_learning/_index.md rename to content/chapters/21_multitarget_learning/_index.md index 4509eac..0ebfe8e 100644 --- a/content/chapters/22_multitarget_learning/_index.md +++ b/content/chapters/21_multitarget_learning/_index.md @@ -1,4 +1,4 @@ --- -title: "Chapter 22: Multitarget Learning" +title: "Chapter 21: Multitarget Learning" --- This chapter introduces multitarget learning techniques. \ No newline at end of file diff --git a/content/chapters/23_online_learning/23-01-intro.md b/content/chapters/22_online_learning/22-01-intro.md similarity index 88% rename from content/chapters/23_online_learning/23-01-intro.md rename to content/chapters/22_online_learning/22-01-intro.md index 03dd046..0585ece 100644 --- a/content/chapters/23_online_learning/23-01-intro.md +++ b/content/chapters/22_online_learning/22-01-intro.md @@ -1,6 +1,6 @@ --- -title: "Chapter 23.01: Introduction" -weight: 23001 +title: "Chapter 22.01: Introduction" +weight: 22001 --- In this chapter we explain the differences between online and batch learning, the extended learning protocol in online learning and the strategies to measure performance in online learning. diff --git a/content/chapters/23_online_learning/23-02-simple.md b/content/chapters/22_online_learning/22-02-simple.md similarity index 81% rename from content/chapters/23_online_learning/23-02-simple.md rename to content/chapters/22_online_learning/22-02-simple.md index 0c97bfe..0b4eb67 100644 --- a/content/chapters/23_online_learning/23-02-simple.md +++ b/content/chapters/22_online_learning/22-02-simple.md @@ -1,6 +1,6 @@ --- -title: "Chapter 23.02: Simple Online Learning Algorithm" -weight: 23002 +title: "Chapter 22.02: Simple Online Learning Algorithm" +weight: 22002 --- In this chapter we introduce the formalization of online learning algorithms and the FTL algorithm. diff --git a/content/chapters/23_online_learning/23-03-ftl.md b/content/chapters/22_online_learning/22-03-ftl.md similarity index 81% rename from content/chapters/23_online_learning/23-03-ftl.md rename to content/chapters/22_online_learning/22-03-ftl.md index 1e0139e..27f40de 100644 --- a/content/chapters/23_online_learning/23-03-ftl.md +++ b/content/chapters/22_online_learning/22-03-ftl.md @@ -1,6 +1,6 @@ --- -title: "Chapter 23.03: Follow the Leader on OLO problems" -weight: 23003 +title: "Chapter 22.03: Follow the Leader on OLO problems" +weight: 22003 --- In this chapter we introduce OLO problems and explain why some FTL might fail on these problems. diff --git a/content/chapters/23_online_learning/23-04-ftrl.md b/content/chapters/22_online_learning/22-04-ftrl.md similarity index 81% rename from content/chapters/23_online_learning/23-04-ftrl.md rename to content/chapters/22_online_learning/22-04-ftrl.md index f27095d..34bb21f 100644 --- a/content/chapters/23_online_learning/23-04-ftrl.md +++ b/content/chapters/22_online_learning/22-04-ftrl.md @@ -1,6 +1,6 @@ --- -title: "Chapter 23.04: Follow the regularized Leader" -weight: 23004 +title: "Chapter 22.04: Follow the regularized Leader" +weight: 22004 --- In this chapter we introduce FTLR as a stable alternative to FTL. diff --git a/content/chapters/23_online_learning/23-05-ftl-oqo.md b/content/chapters/22_online_learning/22-05-ftl-oqo.md similarity index 81% rename from content/chapters/23_online_learning/23-05-ftl-oqo.md rename to content/chapters/22_online_learning/22-05-ftl-oqo.md index 98249f5..0988a44 100644 --- a/content/chapters/23_online_learning/23-05-ftl-oqo.md +++ b/content/chapters/22_online_learning/22-05-ftl-oqo.md @@ -1,6 +1,6 @@ --- -title: "Chapter 23.05: Follow the Leader on OQO problems" -weight: 23005 +title: "Chapter 22.05: Follow the Leader on OQO problems" +weight: 22005 --- In this chapter we prove that FTL works for online quadratic problems. diff --git a/content/chapters/23_online_learning/23-06-oco-1.md b/content/chapters/22_online_learning/22-06-oco-1.md similarity index 84% rename from content/chapters/23_online_learning/23-06-oco-1.md rename to content/chapters/22_online_learning/22-06-oco-1.md index 9968c2a..fb446f6 100644 --- a/content/chapters/23_online_learning/23-06-oco-1.md +++ b/content/chapters/22_online_learning/22-06-oco-1.md @@ -1,6 +1,6 @@ --- -title: "Chapter 23.06: Online Convex optimization 1" -weight: 23006 +title: "Chapter 22.06: Online Convex optimization 1" +weight: 22006 --- In this chapter we introduce the class of online convex optimization problems and derive the online gradient descent as a suitable learning algorithm for such cases. diff --git a/content/chapters/23_online_learning/23-07-oco-2.md b/content/chapters/22_online_learning/22-07-oco-2.md similarity index 84% rename from content/chapters/23_online_learning/23-07-oco-2.md rename to content/chapters/22_online_learning/22-07-oco-2.md index 863e1b0..06ce4a6 100644 --- a/content/chapters/23_online_learning/23-07-oco-2.md +++ b/content/chapters/22_online_learning/22-07-oco-2.md @@ -1,6 +1,6 @@ --- -title: "Chapter 23.07: Online Convex optimization 2" -weight: 23007 +title: "Chapter 22.07: Online Convex optimization 2" +weight: 22007 --- In this chapter we explain the connection between OGD and FTRL via linearization of convex functions and how this implies regret bounds for OGD. diff --git a/content/chapters/23_online_learning/_index.md b/content/chapters/22_online_learning/_index.md similarity index 56% rename from content/chapters/23_online_learning/_index.md rename to content/chapters/22_online_learning/_index.md index 034021f..067fd60 100644 --- a/content/chapters/23_online_learning/_index.md +++ b/content/chapters/22_online_learning/_index.md @@ -1,4 +1,4 @@ --- -title: "Chapter 23: Online Learning" +title: "Chapter 22: Online Learning" --- This chapter introduces online learning. \ No newline at end of file diff --git a/content/chapters/30_feature_selection/30-01-introduction.md b/content/chapters/30_feature_selection/30-01-introduction.md new file mode 100644 index 0000000..c239715 --- /dev/null +++ b/content/chapters/30_feature_selection/30-01-introduction.md @@ -0,0 +1,14 @@ +--- +title: "Chapter 30.01: Introduction" +weight: 30001 +--- +We motivate feature selection and discuss the difference to feature extraction. + + +### Lecture video + +{{< video id="xiVB1EmlU9A" >}} + +### Lecture slides + +{{< pdfjs file="https://github.com/slds-lmu/lecture_sl/raw/main/slides-pdf/slides-fs-introduction.pdf" >}} diff --git a/content/chapters/30_feature_selection/30-02-motivating-examples.md b/content/chapters/30_feature_selection/30-02-motivating-examples.md new file mode 100644 index 0000000..dc3dfba --- /dev/null +++ b/content/chapters/30_feature_selection/30-02-motivating-examples.md @@ -0,0 +1,15 @@ +--- +title: "Chapter 30.02: Motivating Examples" +weight: 30002 +--- +In this section, we explain the practical importance of feature selection and show that models with +integrated selection do not always work. + + +### Lecture video + +{{< video id="1BwgTptjDs4" >}} + +### Lecture slides + +{{< pdfjs file="https://github.com/slds-lmu/lecture_sl/raw/main/slides-pdf/slides-fs-motivating-examples.pdf" >}} diff --git a/content/chapters/30_feature_selection/30-03-filters1.md b/content/chapters/30_feature_selection/30-03-filters1.md new file mode 100644 index 0000000..070b409 --- /dev/null +++ b/content/chapters/30_feature_selection/30-03-filters1.md @@ -0,0 +1,15 @@ +--- +title: "Chapter 30.03: Filter Methods I" +weight: 30003 +--- +We introduce how filter methods work and how they can be used for feature selection. + + + +### Lecture video + +{{< video id="RcDyvExpCSg" >}} + +### Lecture slides + +{{< pdfjs file="https://github.com/slds-lmu/lecture_sl/raw/main/slides-pdf/slides-fs-filters1.pdf" >}} diff --git a/content/chapters/30_feature_selection/30-04-filters2.md b/content/chapters/30_feature_selection/30-04-filters2.md new file mode 100644 index 0000000..3f8e236 --- /dev/null +++ b/content/chapters/30_feature_selection/30-04-filters2.md @@ -0,0 +1,15 @@ +--- +title: "Chapter 30.04: Filter Methods II (Examples and Caveats)" +weight: 30004 +--- +In this section, we discuss how filter methods can be misleading and show how they work in practical applications. + + + +### Lecture video + +{{< video id="X3FpzGnGA7o" >}} + +### Lecture slides + +{{< pdfjs file="https://github.com/slds-lmu/lecture_sl/raw/main/slides-pdf/slides-fs-filters2.pdf" >}} diff --git a/content/chapters/30_feature_selection/30-05-wrapper.md b/content/chapters/30_feature_selection/30-05-wrapper.md new file mode 100644 index 0000000..a9de28d --- /dev/null +++ b/content/chapters/30_feature_selection/30-05-wrapper.md @@ -0,0 +1,15 @@ +--- +title: "Chapter 30.05: Wrapper Methods" +weight: 30005 +--- +This section explains wrapper methods and explains how they can aid feature selection. + + + +### Lecture video + +{{< video id="XmvlHUCGNbc" >}} + +### Lecture slides + +{{< pdfjs file="https://github.com/slds-lmu/lecture_sl/raw/main/slides-pdf/slides-fs-wrapper.pdf" >}} diff --git a/content/chapters/30_feature_selection/_index.md b/content/chapters/30_feature_selection/_index.md new file mode 100644 index 0000000..5eb7c0f --- /dev/null +++ b/content/chapters/30_feature_selection/_index.md @@ -0,0 +1,5 @@ +--- +title: "Extra Chapter: Feature Selection" +--- +This chapter introduces feature selection, i.e., dinding a well-performing, hopefully small set of +features for a task. \ No newline at end of file