Support Vector Machine Algorithm.pptx - Support Vector...

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Support Vector Machine Algorithm
What is Support Vector Machine?
SVM 1. In this algorithm, we plot each data item as a point in n-dimensional space (where n is number of features you have) with the value of each feature being the value of a particular coordinate. 2. Then, we perform classification by finding the hyperplane or set of hyperplanes that differentiate the two classes very well 3. Support Vectors are simply the coordinates of individual observation. Support Vector Machine is a frontier which best segregates the two classes (hyper-plane/ line).
Linear SVMs : 1) Plot each data item as a point in n-dimensional space with the value of each feature being the value of a particular coordinate
2) Find the hyperplane that differentiate the two classes very well Linear SVMs :
“How can we identify the right hyper-plane?” Choose the hyperplane which separates the class very well.

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