'Introduce slack variables' diaporamas de présentation

DATA MINING LECTURE 10

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Data Mining Classification: Alternative Techniques

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Agenda

Agenda. Bayes rule Popular classification methods Logistic regression Linear discriminant analysis (LDA)/QDA and Fisher criteria K-nearest neighbor (KNN) Classification and regression tree (CART) Bagging Boosting Random Forest Support vector machines (SVM)

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Learning Objectives for Section 6.3

Learning Objectives for Section 6.3. Dual Problem: Minimization with Problem Constraints of the Form >. The student will be able to formulate the dual problem. The student will be able to solve minimization problems.

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Learning a Kernel Matrix for Nonlinear Dimensionality Reduction

Learning a Kernel Matrix for Nonlinear Dimensionality Reduction. By K. Weinberger, F. Sha, and L. Saul Presented by Michael Barnathan. The Problem:. Data lies on or near a manifold . Lower dimensionality than overall space. Locally Euclidean.

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Learning a Kernel Matrix for Nonlinear Dimensionality Reduction

Learning a Kernel Matrix for Nonlinear Dimensionality Reduction. By K. Weinberger, F. Sha, and L. Saul Presented by Michael Barnathan. The Problem:. Data lies on or near a manifold . Lower dimensionality than overall space. Locally Euclidean.

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Lecture outline

Lecture outline. Support vector machines. Find a linear hyperplane (decision boundary) that will separate the data. Support Vector Machines. One Possible Solution. Support Vector Machines. Another possible solution. Support Vector Machines. Other possible solutions.

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Lecture outline

Lecture outline. Support vector machines. Find a linear hyperplane (decision boundary) that will separate the data. Support Vector Machines. One Possible Solution. Support Vector Machines. Another possible solution. Support Vector Machines. Other possible solutions.

338 views • 13 slides

Questions and Topics Review Nov. 30, 2010

Questions and Topics Review Nov. 30, 2010. Give an example of a problem that might benefit from feature creation How does DENCLUE form clusters? Why does DENCLUE use grid-cells? What are the main differences between DENCLUE and DBSCAN?

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