SVMs are supervised learning models that we can use to create classifiers and regressors. An SVM solves a system of mathematical equations and finds the best separating boundary between two sets of points. Let's see how to build a linear classifier using an SVM.
Building a linear classifier using SVMs
Getting ready
Let's visualize our data to understand the problem at hand. We will use the svm.py file for this. Before we build the SVM, let's understand our data. We will use the data_multivar.txt file that's already provided to you. Let's see how to to visualize the data:
- Create a new Python file and add the following lines to it (the full code is in the svm.py file which has already been provided...