Вивчайте Challenge: Implementing a Decision Tree

In this challenge, you will use the Titanic dataset, which contains information about passengers on the Titanic, including their age, sex, family size, and more. The goal is to predict whether a passenger 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 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 start coding

You are given a Titanic dataset stored as a DataFrame in the df variable.

Initialize a Decision Tree model and store it in the decision_tree variable.
Create a dictionary for GridSearchCV to iterate through [1, 2, 3, 4, 5, 6, 7] values for max_depth and [1, 2, 4, 6] values for min_samples_leaf, and store it in the param_grid variable.
Initialize and train a GridSearchCV object, set the number of folds to 10, and store the trained model in the grid_cv variable.

Рішення

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 1. Розділ 17

single

Запитати АІ

Запитайте про що завгодно або спробуйте одне із запропонованих запитань, щоб почати наш чат

Свайпніть щоб показати меню


              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())