Computer Programming Notes

Download iPython Notebook Must See this SVM Model : Build a Digit Recognition Model using (SVC)Support Vector Machine Classifier Thanks For Visiting By Er Shrikant Shejwal

Download iPython Notebook What is Support Vector Machine? The objective of the support vector machine algorithm is to find a hyperplane in an N-dimensional space(N — the number of features) that distinctly classifies the data points. Possible hyperplanes To separate the two classes of data points, there are many possible hyperplanes that could be chosen. Our objective is to find a plane that has the maximum margin, i.e the maximum distance between data points of both classes. Maximizing the margin distance provides some reinforcement so that future data points can be classified with more confidence. Hyperplanes and Support Vectors Hyperplanes in 2D and 3D feature space Hyperplanes are decision boundaries that help classify the data points. Data points falling on either side of the hyperplane can be attributed to different classes. Also, the dimension of the hyperplane depends upon the number of features. If the number of input features is 2, then the hyperplane is just a line. If the n