November 2019
Intermediate to advanced
346 pages
9h 36m
English
In the following steps, we will demonstrate how to instantiate, train, and test an XGBoost classifier:
import pandas as pddf = pd.read_csv("file_pe_headers.csv", sep=",")y = df["Malware"]X = df.drop(["Name", "Malware"], axis=1).to_numpy()
from sklearn.model_selection import train_test_splitX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)
from xgboost import XGBClassifierXGB_model_instance = XGBClassifier()XGB_model_instance.fit(X_train, y_train)
from sklearn.metrics import accuracy_scorey_test_pred = XGB_model_instance.predict(X_test) ...