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  3. Machine Learning for Time Series Data in Python

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.