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Lære Challenge: Implementing a Random Forest | Random Forest
Classification with Python

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Challenge: Implementing a Random Forest

In this chapter, you will build a Random Forest using the same titanic dataset.

Also, you will calculate the cross-validation accuracy using the cross_val_score() function

In the end, you will print the feature importances.
The feature_importances_ attribute only holds an array with importances without specifying the name of a feature.
To print the pairs ('name', importance), you can use the following syntax:

python
Opgave

Swipe to start coding

  1. Import the RandomForestClassifier class.
  2. Create an instance of a RandomForestClassifier class with default parameters and train it.
  3. Print the cross-validation score with the cv=10 of a random_forest you just built.
  4. Print each feature's importance along with its name.

Løsning

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book
Challenge: Implementing a Random Forest

In this chapter, you will build a Random Forest using the same titanic dataset.

Also, you will calculate the cross-validation accuracy using the cross_val_score() function

In the end, you will print the feature importances.
The feature_importances_ attribute only holds an array with importances without specifying the name of a feature.
To print the pairs ('name', importance), you can use the following syntax:

python
Opgave

Swipe to start coding

  1. Import the RandomForestClassifier class.
  2. Create an instance of a RandomForestClassifier class with default parameters and train it.
  3. Print the cross-validation score with the cv=10 of a random_forest you just built.
  4. Print each feature's importance along with its name.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

close

Awesome!

Completion rate improved to 3.57

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