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Lectures from 27411 Biological data analysis and chemometrics

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Date: 12/05/2015 21:00 - Duration:

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Multidimensional scaling_27411_Chemometrics

Multidimensional scaling_27411_PCO-NMS_MST_DTU_27411

Date: 12/05/2015 16:14 - Duration: 00:25:52 - Views: 146

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Overview Lecture 2F

The overall modelling approach: Cross validation etc.

Date: 12/05/2015 15:56 - Duration: 00:08:39 - Views: 123

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Overview Lecture 2E

All the methods are shrinking the MLR solution.

Date: 12/05/2015 15:55 - Duration: 00:08:18 - Views: 101

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Overview Lecture 2E

All the methods are shrinking the MLR solution.

Date: 12/05/2015 15:54 - Duration: 00:08:18 - Views: 107

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Overview Lecture 2D

Biased regression methods: Ridge, Lasso, PLS, PCR.

Date: 12/05/2015 15:53 - Duration: 00:14:29 - Views: 114

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Overview Lecture 2C

MLR - the basic model.

Date: 12/05/2015 15:52 - Duration: 00:05:59 - Views: 109

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Overview Lecture 2B

Bias and Variance in prediction, optimal predictor.

Date: 12/05/2015 15:49 - Duration: 00:09:57 - Views: 138

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Overview Lecture 2A

Regression and discrimination, by Per B.B.

Date: 12/05/2015 15:48 - Duration: 00:17:24 - Views: 126

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Overview Lecture 1

Overview of classification in Chemometrics, by Jens Chr. Frisvad.

Date: 12/05/2015 15:47 - Duration: 00:13:57 - Views: 135

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Cluster Analysis

Lecture by Jens Chr. Frisvad on Cluster Analysis.

Date: 12/05/2015 15:45 - Duration: 00:23:42 - Views: 133

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Multidimensional scaling_27411_Chemometrics

Multidimensional scaling_PCO_MDS_NMS in general

Date: 05/05/2015 12:49 - Duration: 00:25:52 - Views: 130

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R-tutorial - exercise data (SHW)

Presenting the two data sets for the exercises.

Date: 13/04/2015 15:57 - Duration: 00:15:25 - Views: 99

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Lec 9C (SHW): Random Forests

Learning from the model: Interpretation. Using ForestFloor - an R-package developed by SHW.

Date: 13/04/2015 15:46 - Duration: 00:16:51 - Views: 121

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R-tutorial, part 2 (SHW).

Random Forests in R.

Date: 13/04/2015 15:23 - Duration: 00:15:27 - Views: 113

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R-tutorial (SHW):; Random forests

How to run Random forests in R. An example.

Date: 13/04/2015 15:21 - Duration: 00:07:53 - Views: 133

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Lec 9B: (SHW): Random Forests

The Tree model, bagging and random forests.

Date: 13/04/2015 15:18 - Duration: 00:19:12 - Views: 125

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Lec 9A: Søren Havelund Welling(SHW): Supervised learning

Supervised learning and classical statistics

Date: 13/04/2015 15:17 - Duration: 00:04:23 - Views: 121

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RTutorial, Discriminant Analysis

Iris data example. Various methods, part 1.

Date: 25/03/2015 21:09 - Duration: 00:17:12 - Views: 131

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RTutorial, Discriminant Analysis

Iris data example. Various methods, part 1.

Date: 25/03/2015 21:09 - Duration: 00:09:46 - Views: 130

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Lec 8H: Discriminant Analysis

Regression, PLS and summary.

Date: 25/03/2015 21:05 - Duration: 00:06:48 - Views: 143

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Lec 8G: Discriminant Analysis

Regression and PLS

Date: 25/03/2015 21:04 - Duration: 00:05:04 - Views: 148

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Lec 8F: Discriminant Analysis

k-Nearest Neighbour

Date: 25/03/2015 21:02 - Duration: 00:07:34 - Views: 152

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Lec 8E: Discriminant Analysis

Relations between Bayes, LDA, QDA and CVA.

Date: 25/03/2015 21:01 - Duration: 00:04:07 - Views: 155

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Lec 8D: Discriminant Analysis

Fisher and CVA.

Date: 25/03/2015 21:00 - Duration: 00:10:19 - Views: 155

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Lec 8C: Discriminant Analysis

LDA and QDA: Linear and Quadratic DA.

Date: 25/03/2015 20:59 - Duration: - Views: 94

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Lec 8B: Discriminant Analysis

Different priors and miss classification costs

Date: 25/03/2015 20:57 - Duration: 00:09:27 - Views: 149

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Lec 8A: Discriminant Analysis

An introduction

Date: 25/03/2015 20:55 - Duration: 00:13:52 - Views: 172

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RTutorial, Ridge and Lasso Regression.

How to predict in R.

Date: 16/03/2015 15:24 - Duration: 00:02:52 - Views: 126

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RTutorial, Lasso Regression.

How to do it in R.

Date: 16/03/2015 15:22 - Duration: 00:07:29 - Views: 128

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RTutorial, Ridge Regression.

How to do it in R.

Date: 16/03/2015 15:20 - Duration: 00:15:14 - Views: 65

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Lec 7H: Ridge Regression

Question to small example.

Date: 16/03/2015 15:19 - Duration: 00:02:29 - Views: 119

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Lec 7I: Ridge and Lasso.

How to analyze data by Ridge and Lasso Regression - the overall approach.

Date: 16/03/2015 15:19 - Duration: 00:03:28 - Views: 129

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Lec 7G: Rddge Regression

A small example.

Date: 16/03/2015 15:17 - Duration: 00:03:45 - Views: 126

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Lec 7F: Ridge and Lasso

L2 and L1 regression methods - an overview.

Date: 16/03/2015 15:17 - Duration: 00:11:52 - Views: 129

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Lec 7E: Ridge Regression

The solution

Date: 16/03/2015 15:15 - Duration: 00:03:34 - Views: 136

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Lec 7C: Ridge Regression

Definition of Ridge Regression

Date: 16/03/2015 15:13 - Duration: 00:07:36 - Views: 137

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Lec 7D: Lasso Regression

Definition of Lasso regression.

Date: 16/03/2015 15:13 - Duration: 00:02:16 - Views: 135

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Lec 7B: MLR and the problem.

MLR produces solutions with too large coefficients.

Date: 16/03/2015 15:11 - Duration: 00:10:05 - Views: 129

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Lec 7A: Optimal predictor?

Finding optimal predictor by CV (cross validation): Bias, variance and model complexity.

Date: 16/03/2015 15:08 - Duration: 00:15:25 - Views: 136

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RTutorial, PLS.

How to use R to analyse data by PLS-regression.

Date: 11/03/2015 11:23 - Duration: 00:20:55 - Views: 139

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Lec 6D. PLS - what is it?

A different description of PLS - a chemometrics perspective.

Date: 11/03/2015 11:22 - Duration: 00:12:20 - Views: 154

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Lec 6C. PLS - how to do it!

A description of the analysis approach when using PLS-regression.

Date: 11/03/2015 11:20 - Duration: 00:13:30 - Views: 71

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Lec 6B. PLS: What is it?

What is pls?

Date: 11/03/2015 11:19 - Duration: 00:14:11 - Views: 152

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Lec 6A. PLS. Motivation

Motivating example: Leslie Salt data.

Date: 11/03/2015 11:18 - Duration: 00:13:23 - Views: 160

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Correspondence analysis_chemometrics

Correspondence analysis_lecture for DTU course 27411

Date: 04/03/2015 16:56 - Duration: 00:26:03 - Views: 151

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RTutorial, PCR

See how to use the 'pcr' function of the 'pls' package.

Date: 24/02/2015 08:25 - Duration: 00:35:23 - Views: 139

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Lec 4F: Cross validation and friends.

Cross validation and other validation and resampling techniques. Model selection. Bias and variance.

Date: 24/02/2015 08:23 - Duration: 00:28:20 - Views: 153

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Lec 4E: PCR - how to do it?

A brief overview of the analysis approach.

Date: 24/02/2015 08:21 - Duration: 00:03:11 - Views: 148

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Lec 4D: What is PCR then.

A final wrap up of this.

Date: 24/02/2015 08:19 - Duration: 00:01:49 - Views: 149

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Lec 4C: Spectral data motivation

A recap of PCA of spectral type data.

Date: 24/02/2015 08:18 - Duration: 00:07:40 - Views: 151

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Lec 4B: Motivating example 1.

See how PCR makes better sense than MLR when the x'es are highly correlated.

Date: 24/02/2015 08:15 - Duration: 00:13:50 - Views: 135

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Lec 4A: What is Principal Component Analysis.

A brief initial ' what is PCR?'

Date: 24/02/2015 08:13 - Duration: 00:03:27 - Views: 178

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Lec 3G: R-tutorial. MLR in R.

Model Validation: residual plotting and modelling non-linerarities and interactions. Predicting new observations in R.

Date: 18/02/2015 10:21 - Duration: 00:20:46 - Views: 136

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Lec 3F: R-tutorial: MLR in R.

Running MLR, stepwise variable elimination and statistical inference.

Date: 18/02/2015 10:19 - Duration: 00:16:36 - Views: 123

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Lec 3E: Multicollinearity

And a perspective towards the dimension reduction techniques later in the course.

Date: 18/02/2015 10:17 - Duration: 00:03:44 - Views: 126

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Lec 3D(part 2): Model validation.

Residual plotting and modelling non-linearities and interactions.

Date: 18/02/2015 10:16 - Duration: 00:11:49 - Views: 138

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Lec 3D(part 1): Model validation.

Start.

Date: 18/02/2015 10:11 - Duration: 00:01:41 - Views: 131

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Lec 3C: Multiple Linear Regression

Computations, Statistical inference and interpretation.

Date: 18/02/2015 10:09 - Duration: 00:22:07 - Views: 138

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Lec 3B: Multiple Linear Regression

Basics: The model and approach.

Date: 18/02/2015 10:07 - Duration: 00:21:01 - Views: 152

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Lec 3A: Exploring the Leslie Salt data

Using R for initial explorative data analysis.

Date: 18/02/2015 09:54 - Duration: 00:19:39 - Views: 140

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Principal Component Analysis_2

PCA_part_2, DTU course 27411

Date: 10/02/2015 10:01 - Duration: 00:34:49 - Views: 170

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Principal Component Analysis_1

PCA, first lecture for DTU course 27411

Date: 10/02/2015 09:59 - Duration: 00:25:18 - Views: 245

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Lec1G: Correlation and covariance

Link between multivariate data and simple correlations.

Date: 02/02/2015 16:00 - Duration: 00:10:49 - Views: 136

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Lec 1F: Lattin Chapter2

A little recap of linear algebra(matrices).

Date: 02/02/2015 15:58 - Duration: 00:17:31 - Views: 125

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Lec 1E: QSAR example

Permeability discrimination of drug candidates.

Date: 02/02/2015 15:57 - Duration: 00:08:26 - Views: 121

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Lec 1D: Food example.

PBB example of Sensory (and other) data on frozen peas.

Date: 02/02/2015 15:54 - Duration: 00:12:01 - Views: 137

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Lec1C: Introduction to Chemometrics, part 2

By Jens Chr. Frisvad

Date: 02/02/2015 15:44 - Duration: 00:18:01 - Views: 139

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Lec 1B: Introduction to Chemometrics, part 1

By Jens Chr. Frisvad

Date: 02/02/2015 15:43 - Duration: 00:20:10 - Views: 156

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Lec 1A: Course welcome.

And practical information.

Date: 02/02/2015 15:42 - Duration: 00:12:35 - Views: 144

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Total duration: 14:42:57