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一种核密度估计，或者称作带宽选择的方法，可以估计二维尺度参数，至于多维以上的估计方法尚在开发，多维情况下个人经验好的方法是多次实验取较好值,kernel density estimation, bandwidth selection, two-dimensional scale parameter can be estimated ,for the multi-dimensional approaches are still under development, multi-dimensiona
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fast and accurate state-of-the-art bivariate kernel density estimator
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Reliable and extremely fast kernel density estimator for one-dimensional data
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machine learning-Density Estimation objects.
parzen - Parzen s windows kernel density estimator
indep - Density estimator which assumes feature independence
bayes - Classifer based on density estimation for each class
gauss - Normal distr
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核密度估计的源码，kernel density estimation，从官方渠道获得-Source kernel density estimation, kernel density estimation
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二维高斯核函数重构
重构方法不依赖于参数化模型-2D Gaussian Kernel Reconstruction
fast and accurate state-of-the-art
bivariate kernel density estimator
with diagonal bandwidth matrix.
The kernel is assumed to be Gaussian.
The two bandwidth parameter
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