Description: 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 distribution density estimator-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 distribution density estimator Platform: |
Size: 14336 |
Author:hossein |
Hits:
Description: 横轴和纵轴，可以将样本点表示出来。由于一般第一、二和三主成分包含的样本的信息较多，
经常选其作为横轴和纵轴。当两个样本差异不大时，他们对应的主成分的得分值差异也不会大，
所以可以凭此对样本进行分类。-The quality of the sample
depends on the accuracy of the density estimator chosen, and it needs to decide the kinds of kernel function and the value of its bandwidth and $\alpha$. Besides
there are some drawback about the relation between the value $\alpha$ and the ratio of cluster and outlier. In the future, the extension of
its techniques to data sets of very high dimensionality is possible by taking into account several properties of high-dimensional spaces. Platform: |
Size: 616448 |
Author:宋云胜 |
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Description: 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 parameters are
chosen optimally without ever
using/assuming a parametric model for the data or any rules of thumb .
Unlike many other procedures, this one
is immune to accuracy failures in the estimation of
multimodal densities with widely separated modes Platform: |
Size: 4096 |
Author:zty |
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Search - Kernel Density Estimator