# import packages import pandas as pd import numpy as np import os re from random import sample from sklearn import datasets from xgboost import XGBClassifier from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score import pickle import m2cgen as m2c
seed = 2020 test_size = 0.3 X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=test_size, random_state=seed) # fit model on training data model = XGBClassifier() model.fit(X_train, y_train)