Classification with neural networks

Now, let's perform our classification task using a neural network. As you will see, the only change necessary in an MLP for it to be able to perform classification is in the output layer:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import os
%matplotlib inline

As always, let's start from scratch and import and prepare our data:

# Loading the dataset
DATA_DIR = '../data'
FILE_NAME = 'credit_card_default.csv'
data_path = os.path.join(DATA_DIR, FILE_NAME)
ccd = pd.read_csv(data_path, index_col="ID")
ccd.rename(columns=lambda x: x.lower(), inplace=True)
ccd.rename(columns={'default payment next month':'default'}, inplace=True)

# getting the groups of features
bill_amt_features = ['bill_amt'+ str(i) for i in range(1,7)]
pay_amt_features = [&apos...