'Global approximation' presentation slideshows

Tuesday, November 20, 2001 William H. Hsu Department of Computing and Information Sciences, KSU

Lecture 25. Instance-Based Learning (IBL): k -Nearest Neighbor and Radial Basis Functions. Tuesday, November 20, 2001 William H. Hsu Department of Computing and Information Sciences, KSU http://www.cis.ksu.edu/~bhsu Readings: Chapter 8, Mitchell. Lecture Outline.

434 views • 18 slides

Tuesday 19 November 2002 William H. Hsu Department of Computing and Information Sciences, KSU

Lecture 23. Instance-Based Learning (IBL): k -Nearest Neighbor and Radial Basis Functions. Tuesday 19 November 2002 William H. Hsu Department of Computing and Information Sciences, KSU http://www.kddresearch.org http://www.cis.ksu.edu/~bhsu Readings: Chapter 8, Mitchell. Lecture Outline.

396 views • 18 slides

Machine Learning Chapter 8. Instance-Based Learning

Machine Learning Chapter 8. Instance-Based Learning. Tom M. Mitchell. Instance Based Learning (1/2). k -Nearest Neighbor Locally weighted regression Radial basis functions Case-based reasoning Lazy and eager learning. Instance-Based Learning (2/2).

1.5k views • 17 slides

Local and Local-Global Approximations

357 views • 16 slides

Wednesday, November 15, 2000 Cecil P. Schmidt Department of Computer Information Sciences, KSU

KDD Group Presentation. Instance-Based Learning. Wednesday, November 15, 2000 Cecil P. Schmidt Department of Computer Information Sciences, KSU http://www.cis.ksu.edu/~cps4444. Presentation Outline. What is Instance Based Learning? k -Nearest Neighbor Learning

137 views • 13 slides