Kernel density estimation
2016-08-23
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KDE is a nonparametric method for estimating the data's probability density function. The intuition behind this method is that the density function is going to be higher in more densely clustered areas and lower in less dense areas, so the density estimate at any given point is the average of a function of the distances from that point to all of the other data points.
matlab
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