Tutorial 2: Heart Disease Classification

Build a model to classify whether a patient has heart disease

Different Kind of Outcome

Unlike Tutorial 1 where we predicted a continuous variable (heart rate in bpm), here we're predicting a binary outcome: does the patient have heart disease? (yes/no). This requires a different type of GLM.

Step 1: Select the Response Variable

Drag Heart Disease to the Response zone on the right.

The response variable (y) is what we're trying to predict or classify.

Why this variable? We want to classify whether patients have heart disease based on their diagnostic measurements.

Available Variables

Your Model

Predictors (X)

Variables that help classify the response

Drop predictors here

Response (y)

What we classify

Drop response here

✓ Great job! You've specified the systematic component for a classification model.
Next step: Choose the link function g(·) that maps to probabilities.

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