Use methods of kernels for clustering and probability dense aproximation
Task 1)
Use a Gaussian Kernel to aproximate the probabilty dense of a uniformly distributed random variable in range [0, 1].
Task 2)
Try to divide 2 classes of 2-D vector data (stars, circles) again with the help of a gaussian kernel.
Task 3)
Try to split data into 2 categories with the K-means algorithm
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Use methods of kernels for clustering and probability dense aproximation
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