Dataset III - Heart Desease

Using sklearn and XGboost for classification
Decision trees for classification

Source: UCI Machine Learning Repository Heart desease dataset

!pip install jovian --upgrade --quiet
import jovian
jovian.commit(project='dataset3-classification', filename='dataset3-classification.ipynb')

[jovian] Attempting to save notebook..
[jovian] Updating notebook "patxigad/dataset3-classification" on https://jovian.ai/
[jovian] Uploading notebook..
[jovian] Capturing environment..
[jovian] Committed successfully! https://jovian.ai/patxigad/dataset3-classification

'https://jovian.ai/patxigad/dataset3-classification'

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 'heart desease' 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/Chapter02/heart_disease.csv')
df.head()