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Learn Challenge: Solving the Task Using Correlation | Covariance and Correlation
Probability Theory Basics

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Challenge: Solving the Task Using Correlation

Task

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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:

  1. Calculate correlations between features and target.
  2. Print these correlations in ascending order.

Solution

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SectionΒ 5. ChapterΒ 3

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book
Challenge: Solving the Task Using Correlation

Task

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:

  1. Calculate correlations between features and target.
  2. Print these correlations in ascending order.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 5. ChapterΒ 3
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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