load_dataset.py

import numpy as np
import pandas as pd
from sklearn.datasets import load_breast_cancer
from sklearn.utils import Bunch

class LoadDataset:
    def __init__(self, which):
        if which == 'bc':
            self.data = load_breast_cancer()
        elif which == 'hp':
            df = pd.read_csv("data/hepatitis.csv")
            #df = df.fillna(method='ffill')
            #df['Class'] = np.where(df['Class'] == 'Yes', 0, 1)
            feature_names = list(df.columns)
            target_names = np.array(['yes', 'no'])

            data = np.array(df.iloc[:, 0:19])
            target = np.array(df['Class'])

            self.data = Bunch(data=data, target=target,
                              target_names=target_names,
                              feature_names=feature_names)
        elif which == 'ildp':
            df = pd.read_csv("data/ildp.csv")
            df = df.fillna(method='ffill')
            df['class'] = np.where(df['class'] == 'Yes', 0, 1)
            feature_names = list(df.columns)
            target_names = np.array(['yes', 'no'])

            data = np.array(df.iloc[:, 0:9])
            target = np.array(df['class'])

            self.data = Bunch(data=data, target=target,
                  target_names=target_names,
                  feature_names=feature_names)