Challenge: Solving the Task Using Correlation
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One of the most important tasks in machine learning is building a linear regression model (you can find more information in the Linear Regression with Python course).
Since we use a linear function in this model, we can use the correlation between features and target to indicate how significant a particular feature is for this model.
We will use the 'Heart Disease Dataset' now: it contains 14
features, including the predicted attribute, which refers to the presence of heart disease in the patient. Your task is to calculate attribute importance using correlation:
- Calculate correlations between features and target.
- Print these correlations in ascending order.
Solution
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Challenge: Solving the Task Using Correlation
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Swipe to start coding
One of the most important tasks in machine learning is building a linear regression model (you can find more information in the Linear Regression with Python course).
Since we use a linear function in this model, we can use the correlation between features and target to indicate how significant a particular feature is for this model.
We will use the 'Heart Disease Dataset' now: it contains 14
features, including the predicted attribute, which refers to the presence of heart disease in the patient. Your task is to calculate attribute importance using correlation:
- Calculate correlations between features and target.
- Print these correlations in ascending order.
Solution
Thanks for your feedback!
Awesome!
Completion rate improved to 3.85single