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:

Завдання

Swipe to show code editor

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

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

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Дякуємо за ваш відгук!

Секція 4. Розділ 3

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

Завдання

Swipe to show code editor

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

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 4. Розділ 3

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

Завдання

Swipe to show code editor

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

Все було зрозуміло?

Дякуємо за ваш відгук!

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

Завдання

Swipe to show code editor

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

Секція 4. Розділ 3