Ensemble Machine Learning Cookbook by Dipayan Sarkar

Author:Dipayan Sarkar [Dipayan Sarkar]
Language: eng
Format: epub
Tags: COM004000 - COMPUTERS / Intelligence (AI) and Semantics, COM044000 - COMPUTERS / Neural Networks, COM042000 - COMPUTERS / Natural Language Processing
Publisher: Packt
Published: 2019-01-31T06:39:03+00:00

Getting ready

In this example, we use a dataset from the UCI ML repository on credit card defaults. This dataset contains the following information:

Default payments

Demographic factors

Credit data

History of payments

Bill statements of credit card clients

The data and the data descriptions are provided in the GitHub folder:

We will start by loading the required libraries and reading our dataset:

import os

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

%matplotlib inline

import seaborn as sns

We set our working folder as follows:

# Set your working directory according to your requirement

os.chdir(".../Chapter 6/Random Forest")

os.getcwd()

Let's now read our data. We will prefix the DataFrame name with df_ so that we can understand it easily:

df_creditcarddata = pd.read_csv("UCI_Credit_Card.csv")

We check the shape of the dataset:

df_creditcarddata.shape

We check the datatypes:

df_creditcarddata.dtypes

We drop the ID column, as this is not required:

df_creditcarddata = df_creditcarddata.drop("ID", axis= 1)

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