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Isabelle Guyon (Clopinet, California) PowerPoint PPT Presentation

Isabelle Guyon (Clopinet, California) - Active Learning Challenge Isabelle Guyon (Clopinet, California) Gavin Cawley (University of East Anglia, UK) Olivier Chapelle (Yahhoo!, California)

Active Learning Challenge Isabelle Guyon (Clopinet, California) Gavin Cawley (University of East Anglia, UK) Olivier Chapelle (Yahhoo!, California)

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Results of the Causality Challenge PowerPoint PPT Presentation

Results of the Causality Challenge - Results of the Causality Challenge Isabelle Guyon, Clopinet Constantin Aliferis and Alexander Statnikov, Vanderbilt Univ. Andr Elisseeff and Jean-Philippe Pellet ...

Results of the Causality Challenge Isabelle Guyon, Clopinet Constantin Aliferis and Alexander Statnikov, Vanderbilt Univ. Andr Elisseeff and Jean-Philippe Pellet ...

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Feature selection methods PowerPoint PPT Presentation

Feature selection methods - Thousands to millions of low level features: select the most relevant one to ... Formalism ( chap. 5) Next few s: Andr Elisseeff ...

Thousands to millions of low level features: select the most relevant one to ... Formalism ( chap. 5) Next few s: Andr Elisseeff ...

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Lecture%202:%20Learning%20without%20Over-learning PowerPoint PPT Presentation

Lecture%202:%20Learning%20without%20Over-learning - Parameters (weights w or a, threshold b) ... A function of the parameters of the ... Shave off unnecessary parameters of your models. The Power of Amnesia ...

Parameters (weights w or a, threshold b) ... A function of the parameters of the ... Shave off unnecessary parameters of your models. The Power of Amnesia ...

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Lecture%203:%20Introduction%20to%20Feature%20Selection PowerPoint PPT Presentation

Lecture%203:%20Introduction%20to%20Feature%20Selection - Soc.religion.christian: god, church, sin. Talk.politics.mideast: israel, armenian, turkish ... Reuters: 21578 news wire, 114 semantic categories. 20 newsgroups: ...

Soc.religion.christian: god, church, sin. Talk.politics.mideast: israel, armenian, turkish ... Reuters: 21578 news wire, 114 semantic categories. 20 newsgroups: ...

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Lecture 1: Learning without Over-learning PowerPoint PPT Presentation

Lecture 1: Learning without Over-learning - the mean square error. x1. x2. Fit / Robustness Tradeoff. x1. x2. 15. Overfitting ... square loss (1- z)2. SVC loss, b=1 max(0, 1-z) logistic loss log(1 e-z) ...

the mean square error. x1. x2. Fit / Robustness Tradeoff. x1. x2. 15. Overfitting ... square loss (1- z)2. SVC loss, b=1 max(0, 1-z) logistic loss log(1 e-z) ...

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Lecture 5: Causality and Feature Selection PowerPoint PPT Presentation

Lecture 5: Causality and Feature Selection - Dependencies represented by edges ... (difficulty of estimation of conditional probabilities for many ... performance is assessed with a given risk functional, not ...

Dependencies represented by edges ... (difficulty of estimation of conditional probabilities for many ... performance is assessed with a given risk functional, not ...

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Suppose we have 5 1D data points PowerPoint PPT Presentation

Suppose we have 5 1D data points - ... A list of SVM implementation can be found at http://www.kernel-machines.org/software.html Some implementation (such as LIBSVM) ...

... A list of SVM implementation can be found at http://www.kernel-machines.org/software.html Some implementation (such as LIBSVM) ...

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Introduction to Machine Learning PowerPoint PPT Presentation

Introduction to Machine Learning - DNA fingerprinting. 6. Computer / Internet. Computer interfaces: Troubleshooting wizards ... m lines = patterns (data points, examples): samples, patients, ...

DNA fingerprinting. 6. Computer / Internet. Computer interfaces: Troubleshooting wizards ... m lines = patterns (data points, examples): samples, patients, ...

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Feature%20selection%20and%20causal%20discovery%20fundamentals%20and%20applications PowerPoint PPT Presentation

Feature%20selection%20and%20causal%20discovery%20fundamentals%20and%20applications - Talk.politics.mideast: israel, armenian, turkish. Talk.religion.misc: jesus, god, jehovah ... Reuters: 21578 news wire, 114 semantic categories. 20 newsgroups: ...

Talk.politics.mideast: israel, armenian, turkish. Talk.religion.misc: jesus, god, jehovah ... Reuters: 21578 news wire, 114 semantic categories. 20 newsgroups: ...

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Feature selection methods - Feature selection methods

Feature selection methods

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Learning Machines and Teaching Machines PowerPoint PPT Presentation

Learning Machines and Teaching Machines - Videos. Games/interactive software. Children/adult activities: 'kitchen counter demos' ... Decision making. Control. Survival. Creation. Challenges. Challenges ...

Videos. Games/interactive software. Children/adult activities: 'kitchen counter demos' ... Decision making. Control. Survival. Creation. Challenges. Challenges ...

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Support Vector Regression PowerPoint PPT Presentation

Support Vector Regression - Title: PowerPoint Presentation Last modified by: Created Date: 1/1/1601 12:00:00 AM Document presentation format: Other titles

Title: PowerPoint Presentation Last modified by: Created Date: 1/1/1601 12:00:00 AM Document presentation format: Other titles

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Lecture 3: Embedded methods PowerPoint PPT Presentation

Lecture 3: Embedded methods - ... Usually order features (individual feature ranking or nested subsets of ... Let us consider the following set of functions parameterized by and where {0,1}n ...

... Usually order features (individual feature ranking or nested subsets of ... Let us consider the following set of functions parameterized by and where {0,1}n ...

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Lecture 2: Introduction to Feature Selection PowerPoint PPT Presentation

Lecture 2: Introduction to Feature Selection - Talk.politics.mideast: israel, armenian, turkish. Talk.religion.misc: jesus, god, jehovah ... Reuters: 21578 news wire, 114 semantic categories. 20 newsgroups: ...

Talk.politics.mideast: israel, armenian, turkish. Talk.religion.misc: jesus, god, jehovah ... Reuters: 21578 news wire, 114 semantic categories. 20 newsgroups: ...

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Lecture 1: Introduction to Machine Learning PowerPoint PPT Presentation

Lecture 1: Introduction to Machine Learning - ... P. Hart, and D. Stork. Standard pattern recognition textbook. ... Linear Discriminants and Support Vector Machines, I. Guyon and D. Stork, In Smola et al Eds. ...

... P. Hart, and D. Stork. Standard pattern recognition textbook. ... Linear Discriminants and Support Vector Machines, I. Guyon and D. Stork, In Smola et al Eds. ...

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RESULTS OF THE WCCI 2006 PowerPoint PPT Presentation

RESULTS OF THE WCCI 2006 - GINA: Kari Torkkola & Eugene Tuv with ACE RLSC. HIVA: Gavin Cawley with Final #3 (corrected) ... GINA. SYLVA. HIVA. NOVA. Part III. RESULT ANALYSIS. What did ...

GINA: Kari Torkkola & Eugene Tuv with ACE RLSC. HIVA: Gavin Cawley with Final #3 (corrected) ... GINA. SYLVA. HIVA. NOVA. Part III. RESULT ANALYSIS. What did ...

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Lecture 2: Introduction to Feature Selection - More trainings at each step, but fewer steps. ... Floating search (SFFS and SBFS): One step of SFS (resp. SBS), then SBS (resp. ...

More trainings at each step, but fewer steps. ... Floating search (SFFS and SBFS): One step of SFS (resp. SBS), then SBS (resp. ...

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Une introduction aux machines PowerPoint PPT Presentation

Une introduction aux machines - Une introduction aux machines vecteurs supports (SVM) Adapt de Martin Law, Antoine Cornu jols et autres sources sur Internet

Une introduction aux machines vecteurs supports (SVM) Adapt de Martin Law, Antoine Cornu jols et autres sources sur Internet

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KDD%20Cup%202009 PowerPoint PPT Presentation

KDD%20Cup%202009 - About 75% ensemble methods (1/3 boosting, 1/3 bagging, 1/3 other). About 10% used unscrambling. ... boosting decision tree technology, bagging also used. ...

About 75% ensemble methods (1/3 boosting, 1/3 bagging, 1/3 other). About 10% used unscrambling. ... boosting decision tree technology, bagging also used. ...

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Lecture 5: Causality and Feature Selection - Genetic factor1. Smoking. Lung cancer. Immediate causes (parents) Smoking. Anxiety. Lung cancer ... Genetic factor1. Hormonal factor. Metastasis (b) Other ...

Genetic factor1. Smoking. Lung cancer. Immediate causes (parents) Smoking. Anxiety. Lung cancer ... Genetic factor1. Hormonal factor. Metastasis (b) Other ...

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Feature Selection and Causal discovery PowerPoint PPT Presentation

Feature Selection and Causal discovery - Feature selection may benefit from introducing a notion of causality: ... Univariate feature selection often yields better accuracy results than ...

Feature selection may benefit from introducing a notion of causality: ... Univariate feature selection often yields better accuracy results than ...

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Feature Selection and Causality Inference PowerPoint PPT Presentation

Feature Selection and Causality Inference - How are we going to make progress? Feature Selection ... tissues (tumor= G3/4, control= NL, Dysplasia, BPH), U133A array (20,000 genes) ...

How are we going to make progress? Feature Selection ... tissues (tumor= G3/4, control= NL, Dysplasia, BPH), U133A array (20,000 genes) ...

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A Simple Introduction to Support Vector Machines PowerPoint PPT Presentation

A Simple Introduction to Support Vector Machines - Each iteration of SMO picks a pair of (ai,aj) and solve the QP with these two ... Classification can become easier with a proper transformation. ...

Each iteration of SMO picks a pair of (ai,aj) and solve the QP with these two ... Classification can become easier with a proper transformation. ...

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A Simple Introduction to Support Vector Machines - Martin Law. Lecture for CSE 802. Department of Computer Science and Engineering ... CSE 802. Prepared by Martin Law. 4. What is a good Decision Boundary? ...

Martin Law. Lecture for CSE 802. Department of Computer Science and Engineering ... CSE 802. Prepared by Martin Law. 4. What is a good Decision Boundary? ...

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Lab 1 - Why is the LOO error sometimes larger than the training and test error? ... testD = data(rand(3,8), [-1 -1 1]'); tresu = test(model, testD) ...

Why is the LOO error sometimes larger than the training and test error? ... testD = data(rand(3,8), [-1 -1 1]'); tresu = test(model, testD) ...

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Text Classification with Support Vector Machine PowerPoint PPT Presentation

Text Classification with Support Vector Machine - a collection of xml documents, and. Each document contains an ... 02 Military Aircraft Operations. 03 Aircraft. 01 Helicopters. 02 Bombers. 02--Agriculture ...

a collection of xml documents, and. Each document contains an ... 02 Military Aircraft Operations. 03 Aircraft. 01 Helicopters. 02 Bombers. 02--Agriculture ...

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Introduction to Support Vector Machines PowerPoint PPT Presentation

Introduction to Support Vector Machines - Andrew would be delighted if you found this source material ... http://mathworld.wolfram.com/Point-LineDistance2-Dimensional.html. In our case, w1*x1 w2*x2 b=0, ...

Andrew would be delighted if you found this source material ... http://mathworld.wolfram.com/Point-LineDistance2-Dimensional.html. In our case, w1*x1 w2*x2 b=0, ...

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Feature Selection Methods - ... Determine roots to det(C- I)=0, roots are eigenvalues Check out any math book such as Elementary Linear Algebra by Howard Anton, ...

... Determine roots to det(C- I)=0, roots are eigenvalues Check out any math book such as Elementary Linear Algebra by Howard Anton, ...

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A Simple Introduction to Support Vector Machines - A Simple Introduction to Support Vector Machines Martin Law Lecture for CSE 802 Department of Computer Science and Engineering Michigan State University

A Simple Introduction to Support Vector Machines Martin Law Lecture for CSE 802 Department of Computer Science and Engineering Michigan State University

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Negative Results and Open Problems PowerPoint PPT Presentation

Negative Results and Open Problems - A wealth of knowledge is lost. ... 1967 - Cover-Hart: Nearest neighbors. 1982 - Hopfield nets, distributed associative memories. ...

A wealth of knowledge is lost. ... 1967 - Cover-Hart: Nearest neighbors. 1982 - Hopfield nets, distributed associative memories. ...

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A Simple Introduction to Support Vector Machines - A Simple Introduction to Support Vector Machines. Martin Law. Lecture for CSE 802 ... SVMs became popular because of success in handwritten digit recognition ...

A Simple Introduction to Support Vector Machines. Martin Law. Lecture for CSE 802 ... SVMs became popular because of success in handwritten digit recognition ...

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Extrinsic Regularization in Parameter Optimization for Support Vector Machines PowerPoint PPT Presentation

Extrinsic Regularization in Parameter Optimization for Support Vector Machines - Title: Slide 1 Author: Matthew D. Boardman Last modified by: Matthew D. Boardman Created Date: 6/1/2006 3:30:16 PM Document presentation format: On-screen Show

Title: Slide 1 Author: Matthew D. Boardman Last modified by: Matthew D. Boardman Created Date: 6/1/2006 3:30:16 PM Document presentation format: On-screen Show

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An Introduction to Support Vector Machines PowerPoint PPT Presentation

An Introduction to Support Vector Machines - What is a good decision boundary? Two classes, not linearly separable ... Sigmoid with parameter and. It does not satisfy the Mercer condition on all and ...

What is a good decision boundary? Two classes, not linearly separable ... Sigmoid with parameter and. It does not satisfy the Mercer condition on all and ...

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An Introduction to Support Vector Machines - Example of SVM Applications: Handwriting Recognition. 11/4/09. CSE 802. Prepared by Martin Law ... correlation analysis, kernel k-means, 1-class SVM are some examples ...

Example of SVM Applications: Handwriting Recognition. 11/4/09. CSE 802. Prepared by Martin Law ... correlation analysis, kernel k-means, 1-class SVM are some examples ...

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Text Classification with Support Vector Machine - a list of subject areas. 25 broad subject fields, divided ... 04--Atmospheric Sciences. 05--Behavioral and Social Sciences. 06--Biological and Medical Sciences ...

a list of subject areas. 25 broad subject fields, divided ... 04--Atmospheric Sciences. 05--Behavioral and Social Sciences. 06--Biological and Medical Sciences ...

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A Simple Introduction to Support Vector Machines - Department of Computer Science and Engineering. Michigan State University. 9/20/09 ... we can just regard the QP solver as a 'black-box' without bothering how it works ...

Department of Computer Science and Engineering. Michigan State University. 9/20/09 ... we can just regard the QP solver as a 'black-box' without bothering how it works ...

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Baseline Methods for the Feature Extraction Class PowerPoint PPT Presentation

Baseline Methods for the Feature Extraction Class - Title: PowerPoint Presentation Author: Isabelle Guyon Last modified by: Isabelle Guyon Created Date: 2/8/2006 8:42:05 PM Document presentation format

Title: PowerPoint Presentation Author: Isabelle Guyon Last modified by: Isabelle Guyon Created Date: 2/8/2006 8:42:05 PM Document presentation format

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Ensemble of ensemble of tree and neural network PowerPoint PPT Presentation

Ensemble of ensemble of tree and neural network - Ensemble of ensemble of tree and neural network Louis Duclos-Gosselin Plan of the presentation Introduction General Model Conclusion Introduction This type of model ...

Ensemble of ensemble of tree and neural network Louis Duclos-Gosselin Plan of the presentation Introduction General Model Conclusion Introduction This type of model ...

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Bayesian network models of Biological signaling pathways PowerPoint PPT Presentation

Bayesian network models of Biological signaling pathways - Bayesian network models of Biological signaling pathways karensachs@stanford.edu * Important for discovering novel cross talk between pathways or to study effects of ...

Bayesian network models of Biological signaling pathways karensachs@stanford.edu * Important for discovering novel cross talk between pathways or to study effects of ...

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A Simple Introduction to Support Vector Machines - It does not satisfy the Mercer condition on all k and q. 9/8/09. CSE 802. Prepared by Martin Law ... needs to satisfy the Mercer function, i.e., the function ...

It does not satisfy the Mercer condition on all k and q. 9/8/09. CSE 802. Prepared by Martin Law ... needs to satisfy the Mercer function, i.e., the function ...

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Lab 1 - Baseline error rates (errate): Training and testing on various data splits with simple methods. ... Best frac. feat. Visualization. 1) Create a heatmap of the ...

Baseline error rates (errate): Training and testing on various data splits with simple methods. ... Best frac. feat. Visualization. 1) Create a heatmap of the ...

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Lecture 3: Embedded methods - Feature selection for linear system is NP hard ... Springer, 2006. http://clopinet.com/fextract-book. Book of the NIPS 2003 challenge ...

Feature selection for linear system is NP hard ... Springer, 2006. http://clopinet.com/fextract-book. Book of the NIPS 2003 challenge ...

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