Exercise

Build a classification model

While eye-balling differences is a useful way to gain an intuition for the data, let's see if you can operationalize things with a model. In this exercise, you will use each repetition as a datapoint, and each moment in time as a feature to fit a classifier that attempts to predict abnormal vs. normal heartbeats using only the raw data.

We've split the two DataFrames (normal and abnormal) into X_train, X_test, y_train, and y_test.

Instructions

100 XP

Create an instance of the Linear SVC model and fit the model using the training data.
Use the testing data to generate predictions with the model.
Score the model using the provided code.