Question: Why the sum "value" isn't equal to the number of "samples" in scikit-learn RandomForestClassifier?
I built a random forest by RandomForestClassifier and plot the decision trees. What does the parameter "value" (pointed by red arrows) mean? And why python error the sum of two numbers in the  doesn't equal to the number of "samples"? I saw some other examples, the sum of two numbers in the  equals to the number of "samples". Why in my case, it doesn't?
df = pd.read_csv("Dataset.csv") df.drop(['Flow ID', 'Inbound'], axis=1, inplace=True) df.replace([np.inf, -np.inf], np.nan, inplace=True) df.dropna(inplace = True) df.Label[df.Label == 'BENIGN'] = 0 df.Label[df.Label == 'DrDoS_LDAP'] = 1 Y = df["Label"].values Y = Y.astype('int') X = df.drop(labels = ["Label"], axis=1) X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.5) model = RandomForestClassifier(n_estimators = 20) model.fit(X_train, Y_train) Accuracy = model.score(X_test, Y_test) for i in range(len(model.estimators_)): fig = plt.figure(figsize=(15,15)) tree.plot_tree(model.estimators_[i], feature_names = df.columns, class_names = ['Benign', 'DDoS']) plt.savefig('.\\TheForest\\T'+str(i))