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3 years ago

Dataset I - Bike rentals

  • Using sklearn and XGboost Linear Regression
  • Decision tree regressor
  • Random forest regressor
  • AdaBoost regressor
  • Gradient boosting

Source: UCI Machine Learning Repository Dataset

import jovian
jovian.commit(project='dataset1-lr', filename='dataset1-lr.ipynb')
[jovian] Update Available: 0.2.28 --> 0.2.32 [jovian] Run `!pip install jovian --upgrade` to upgrade
[jovian] Attempting to save notebook.. [jovian] Updating notebook "patxigad/dataset1-lr" on https://jovian.ai/ [jovian] Uploading notebook.. [jovian] Capturing environment.. [jovian] Committed successfully! https://jovian.ai/patxigad/dataset1-lr 
'https://jovian.ai/patxigad/dataset1-lr'

Getting the data

# main imports
import pandas as pd
import datetime as dt
import numpy as np

import seaborn as sns
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline

sns.set_style('darkgrid')
matplotlib.rcParams['font.size'] = 14
matplotlib.rcParams['figure.figsize'] = (9, 5)
matplotlib.rcParams['figure.facecolor'] = '#00000000'

# silence warnings
import warnings
warnings.filterwarnings('ignore')
# upload 'bike_rentals' to DF and display first few rows
df = pd.read_csv('https://media.githubusercontent.com/media/PacktPublishing/'
                 'Hands-On-Gradient-Boosting-with-XGBoost-and-Scikit-learn/master/Chapter01/bike_rentals.csv')
df.head()