# Plot the decision boundary for a non-linear SVM problem: def plot_decision_boundary (model, ax = None): if ax is None: ax = plt. gca xlim = ax. get_xlim ylim = ax. get_ylim # create grid to evaluate model: x = np. linspace (xlim [0], xlim [1], 30) y = np. linspace (ylim [0], ylim [1], 30) Y, X = np. meshgrid (y, x) # shape data: xy = np ...

How to reset steelseries keyboardOct 29, 2017 · The SVM model has 2 paramaters a) C – Large C (less regularization), more regularization b) gamma – Small gamma has larger decision boundary with more misclassfication, and larger gamma has tighter decision boundary. The R code below computes the accuracy as the regularization paramater is changed

We discussed the SVM algorithm in our last post. In this post we will try to build a SVM classification model in Python. SVM on Python. There are multiple SVM libraries available in Python. The package ‘Scikit’ is the most widely used for machine learning. There is a function called svm() within ‘Scikit’ package.