sklearn decision tree split을 2, 50로 설정하고 accuracy를 비교한다. import sys from class_vis import prettyPicture from prep_terrain_data import makeTerrainData import matplotlib.pyplot as plt import numpy as np import pylab as pl features_train, labels_train, features_test, labels_test = makeTerrainData() ########################## DECISION TREE ################################# ### your code goes here--now create 2 decision tree classifiers, ### one with min_samples_split=2 and one with min_samples_split=50 ### compute the accuracies on the testing data and store ### the accuracy numbers to acc_min_samples_split_2 and ### acc_min_samples_split_50,...