A Practical Guide to Machine Learning with Python/

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Implementation of Gradient Boosting Regressor

Implementation of Gradient Boosting Regressor

Let's implement gradient boosting for the regression problem.

We'll cover the following...

Exercise In this exercise, you will use gradient boosting to predict a numeric target output (regression) for the nightly fee of Airbnb accommodation in Berlin, Germany. After devising our initial model, we will then test a sample listing.

1) Import libraries

Import the following libraries:

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#1- Import libraries
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn import ensemble
from sklearn.metrics import mean_absolute_error

Note: Codes of further steps won’t include codes of previous steps. They’re already appended at the backend for you.

2) Import dataset

For this regression exercise, we will use the Berlin Airbnb dataset, which can be downloaded from Kaggle. ...