In the previous scenario, you've seen the typical Machine Learning process, from loading the data, splitting it, training and evaluation. This scenario is the continuation of the introduced concepts. This time you will try to classify the data that are not easily separable with the straight line.
The primary purpose of this scenario is for you to practice running the Machine Learning process with some Python code. This time we will use the data which classes cannot be easily separated with the straight line.
The following picture is visualising the data. Similarly as in the previous scenario, the (x1, x2) coefficients are the examples features, while the colour indicates the labels (red and blue).
The code you'll be working with is in the
classification.py file. We have also provided some helper functions which are available in the
The first thing you need to do is to read the data. Use
read_and_visualise_data and load them into data DataFrame. We're using pandas in our code, so you may find it useful to learn how does the indexing work.