这将数据分类为决策树。已经创建了决策树,但我无法查看决策树。
import numpy as np
from sklearn import linear_model, datasets, tree
import matplotlib.pyplot as plt
iris = datasets.load_iris()
f = open('decision_tree_data.txt')
x_train = []
y_train = []
for line in f:
line = np.asarray(line.split(),dtype = np.float32)
x_train.append(line[:-1])
y_train.append(line[:-1])
x_train = np.asmatrix(x_train)
y_train = np.asmatrix(y_train)
model = tree.DecisionTreeClassifier()
model.fit(x_train,y_train)
from sklearn.externals.six import StringIO
import pydot
from IPython.display import Image
dot_data = StringIO()
tree.export_graphviz(model, out_file=dot_data,
feature_names=iris.feature_names,
class_names=iris.target_names,
filled=True, rounded=True,
special_characters=True)
graph = pydot.graph_from_dot_data(dot_data.getvalue())
Image(graph.create_png())
graph
是一个列表,而不是预期的pydot对象。你是否忘记进行todot
转换了?抱歉,我对这个包不是很熟悉。 - Prune