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

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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:

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

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Challenge: Solving the Task Using Correlation

Oppgave

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.

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

close

Awesome!

Completion rate improved to 3.85

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