Python for Finance Cookbook

How to do it...

Execute the following steps to create a stacked ensemble.

1. Import the libraries:

import pandas as pdfrom sklearn.model_selection import (train_test_split,                                      StratifiedKFold)from sklearn import metricsfrom sklearn.preprocessing import StandardScalerfrom sklearn.naive_bayes import GaussianNBfrom sklearn.neighbors import KNeighborsClassifierfrom sklearn.tree import DecisionTreeClassifierfrom sklearn.ensemble import StackingClassifierfrom sklearn.linear_model import LogisticRegression

2. Load and preprocess the data:

RANDOM_STATE = 42k_fold = StratifiedKFold(5, shuffle=True, random_state=42)df = pd.read_csv('credit_card_fraud.csv')X = df.copy()y = X.pop('Class')X_train, X_test, y_train, y_test = train_test_split(X, y,  test_size=0.2, ...