Grid search is good for tuning hyper-parameters. Hyper-parameters are parameters that are not directly learnt within estimators. We will compare the SVM models for different C and gamma values using Gridsearch. Refer to the blog on SVM if you want to learn more about Support Vector Machines. We will directly dive into a practical example of breast cancer classifier problem and optimizing the classifier using […]
Support Vector Machines
Support Vector Machines are supervised learning models which can be used for classification as well as regression problems. For classification, the data is represented as a point in space and the classification is achieved by dividing the points by a hyperplane so that it has the maximum distance from the two classes being separated. The margin of separation is with respect to the vector points […]