Challenge: Implementing a Decision Tree

In this challenge, you will use the titanic dataset. It holds information about passengers on the Titanic, including their age, sex, family size, etc. And the task is to predict whether a person survived or not.


              1234
            
import pandas as pd

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b71ff7ac-3932-41d2-a4d8-060e24b00129/titanic.csv') 
print(df.head())

To implement the Decision Tree, you can use the DecisionTreeClassifier from the sklearn.

Your task is to build a Decision Tree and find the best max_depth and min_samples_leaf using grid search.

Завдання

Swipe to show code editor

Import the DecisionTreeClassifier class from sklearn.tree.
Assign an instance of DecisionTreeClassifier to the decision_tree variable.
Create a dictionary for a GridSearchCV to run through [1, 2, 3, 4, 5, 6, 7] values of max_depth and [1, 2, 4, 6] values of min_samples_leaf.
Create a GridSearchCV object and train it.

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 3. Розділ 4

Challenge: Implementing a Decision Tree


              1234
            
import pandas as pd

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b71ff7ac-3932-41d2-a4d8-060e24b00129/titanic.csv') 
print(df.head())

To implement the Decision Tree, you can use the DecisionTreeClassifier from the sklearn.

Your task is to build a Decision Tree and find the best max_depth and min_samples_leaf using grid search.

Завдання

Swipe to show code editor

Import the DecisionTreeClassifier class from sklearn.tree.
Assign an instance of DecisionTreeClassifier to the decision_tree variable.
Create a dictionary for a GridSearchCV to run through [1, 2, 3, 4, 5, 6, 7] values of max_depth and [1, 2, 4, 6] values of min_samples_leaf.
Create a GridSearchCV object and train it.

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 3. Розділ 4

Challenge: Implementing a Decision Tree


              1234
            
import pandas as pd

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b71ff7ac-3932-41d2-a4d8-060e24b00129/titanic.csv') 
print(df.head())

To implement the Decision Tree, you can use the DecisionTreeClassifier from the sklearn.

Your task is to build a Decision Tree and find the best max_depth and min_samples_leaf using grid search.

Завдання

Swipe to show code editor

Import the DecisionTreeClassifier class from sklearn.tree.
Assign an instance of DecisionTreeClassifier to the decision_tree variable.
Create a dictionary for a GridSearchCV to run through [1, 2, 3, 4, 5, 6, 7] values of max_depth and [1, 2, 4, 6] values of min_samples_leaf.
Create a GridSearchCV object and train it.

Все було зрозуміло?

Дякуємо за ваш відгук!


              1234
            
import pandas as pd

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b71ff7ac-3932-41d2-a4d8-060e24b00129/titanic.csv') 
print(df.head())

To implement the Decision Tree, you can use the DecisionTreeClassifier from the sklearn.

Your task is to build a Decision Tree and find the best max_depth and min_samples_leaf using grid search.

Завдання

Swipe to show code editor

Import the DecisionTreeClassifier class from sklearn.tree.
Assign an instance of DecisionTreeClassifier to the decision_tree variable.
Create a dictionary for a GridSearchCV to run through [1, 2, 3, 4, 5, 6, 7] values of max_depth and [1, 2, 4, 6] values of min_samples_leaf.
Create a GridSearchCV object and train it.

Секція 3. Розділ 4