Compressed Firmware Classification Based on Extra Trees and Doc2Vec

Table 2

Model parameters.

Model	Framework	Parameters
Decision Tree	Scikit-learn	criterion = “entropy,” random_state = 0
Random Forest	Scikit-learn	criterion = “entropy,” min_samples_leaf = 2, class_weight = “balanced”
XGBoost	Scikit-learn	random_state = 27
Extra Trees	Scikit-learn	Default
SVM	Scikit-learn	Default
Doc2Vec	Gensim	min_count = 1, window = 5, size = 10, sample = 1e-3, negative = 5, workers = 4