Evaluation of few methods to apply Gaussian Blur on an Image.
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Updated
Mar 15, 2022 - MATLAB
Evaluation of few methods to apply Gaussian Blur on an Image.
Implementation of Kernel-Density-Estimation (KDE) with Matlab
We use support vector machines (SVMs) with various example 2D datasets. Experimenting with these datasets will help us gain an intuition of how SVMs work and how to use a Gaussian kernel with SVMs. In the next half of the exercise, we use support vector machines to build a spam classifier.
Primal-Dual algorithm for smooth regularization of non-smooth optimization functions
Fraud detection over twitter feed data
Classification on the Web Spam Dataset using Percepton and Kernel Perceptron with Polynomial, Gaussian, Exponential and Laplacian Kernels.
It is based on support vector machines ,first we used linear kernel for lesser featured dataset, Gaussian kernel for more complex dataset.
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