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Nearest neighbor rule - PowerPoint PPT Presentation

Lecture outline

Lecture outline

Lecture outline. Nearest-neighbor search in low dimensions kd-trees Nearest-neighbor search in high dimensions LSH Applications to data mining. Definition. Given: a set X of n points in R d Nearest neighbor: for any query point q ? R d return the point x ? X minimizing D(x,q)

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559 views • 55 slides
Lecture outline

Lecture outline

Lecture outline. Nearest-neighbor search in low dimensions kd-trees Nearest-neighbor search in high dimensions LSH Applications to data mining. Definition. Given: a set X of n points in R d Nearest neighbor: for any query point q ? R d return the point x ? X minimizing D(x,q)

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713 views • 51 slides
Lecture outline

Lecture outline

Lecture outline. Nearest-neighbor search in low dimensions kd-trees Nearest-neighbor search in high dimensions LSH Applications to data mining. Definition. Given: a set X of n points in R d Nearest neighbor: for any query point q ? R d return the point x ? X minimizing D(x,q)

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675 views • 51 slides
Classification of Microarray data

Classification of Microarray data

Classification of Microarray data. Chris Holmes With thanks to: Jean Yang. Classification. Task: assign objects to classes (groups) on the basis of measurements made on the objects ( features) Unsupervised: classes unknown, want to discover them from the data (cluster analysis)

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551 views • 36 slides
A Study of the Behavior of Several Methods for Balancing Machine Learning Training Data

A Study of the Behavior of Several Methods for Balancing Machine Learning Training Data

A Study of the Behavior of Several Methods for Balancing Machine Learning Training Data. Author: Gustavo E. A. Batista Presenter: Hui Li University of Ottawa. Contents. Introduction Why Learning from Imbalanced data sets might be difficult? 10 Methods Experimental Evaluation Conclusion.

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848 views • 35 slides
Chapter 4 (part 2): Non-Parametric Classification (Sections 4.3-4.5)

Chapter 4 (part 2): Non-Parametric Classification (Sections 4.3-4.5)

Pattern Classification All materials in these slides were taken from Pattern Classification (2nd ed) by R. O. Duda, P. E. Hart and D. G. Stork, John Wiley & Sons, 2000 with the permission of the authors and the publisher. Chapter 4 (part 2): Non-Parametric Classification (Sections 4.3-4.5).

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324 views • 20 slides

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