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Today we discussed the Parzen window method for estimating the probability density function at a point x of the feature space using samples drawn. | Today we discussed the Parzen window method for estimating the probability density function at a point x of the feature space using samples drawn. | ||
| − | + | ==Relevant Rhea Pages== | |
| + | *[[Lecture_14_-_ANNs%2C_Non-parametric_Density_Estimation_(Parzen_Window)_Old_Kiwi|Lecture 14, ECE662 Spring 2008]] | ||
| + | *[[Lecture_15_-_Parzen_Window_Method_Old_Kiwi|Lecture 15, ECE662 Spring 2008]] | ||
| + | *[[Lecture_16_-_Parzen_Window_Method_and_K-nearest_Neighbor_Density_Estimate_Old_Kiwi|Lecture 16, ECE662, Spring 2008]] | ||
Previous: [[Lecture16ECE662S12|Lecture 16]] | Previous: [[Lecture16ECE662S12|Lecture 16]] | ||
Revision as of 13:37, 8 March 2012
Lecture 17 Blog, ECE662 Spring 2012, Prof. Boutin
Tuesday March 6, 2012 (Week 9)
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Today we discussed the Parzen window method for estimating the probability density function at a point x of the feature space using samples drawn.
Relevant Rhea Pages
Previous: Lecture 16
Next: Lecture 18
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