error: InvocationException: GraphViz’s executables not found The
source code is as follows
from itertools import product
import numpy as np
import matplotlib.pyplot as plt
from sklearn import datasets
from sklearn.tree import DecisionTreeClassifier
# Still using the iris data that comes with it
iris = datasets.load_iris()
X = iris.data[:, [0, 2]]
y = iris.target
# Training the model, limiting the maximum depth of the tree to 4
clf = DecisionTreeClassifier(max_depth=4)
#Fitting the model
clf.fit(X, y)
# draw
x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1
y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1
xx, yy = np.meshgrid(np.arange(x_min, x_max, 0.1),
np.arange(y_min, y_max, 0.1))
Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])
Z = Z.reshape(xx.shape)
plt.contourf(xx, yy, Z, alpha=0.4)
plt.scatter(X[:, 0], X[:, 1], c=y, alpha=0.8)
plt.show()
There is no problem up to here, then start generating the image of the spanning tree, here is the code
from IPython.display import Image
from sklearn import tree
import pydotplus
dot_data = tree.export_graphviz(clf, out_file=None,
feature_names=iris.feature_names,
class_names=iris.target_names,
filled=True, rounded=True,
special_characters=True)
graph = pydotplus.graph_from_dot_data(dot_data)
Image(graph.create_png())
I started to report errors . I
InvocationException: GraphViz's executables not found
learned through Baidu that the environment variables of graphviz were not configured properly,
but I didn’t know where my graphviz was installed,
so I used everything (a very useful software for finding files) to find my graphviz in the bin file. The location
and then edit the environment variables
and finally successfully run the code
Similar Posts:
- AttributeError: ‘_csv.reader’ object has no attribute ‘next’ [How to Solve]
- Name Error: name ‘yolo_head’ is not defined [How to Solve]
- How to Solve graphviz run Error in Pychart
- Mac uses graphviz package to report error failed to execute posixpath (‘dot ‘)
- Pycharm Error: ImportError: No module named model_selection
- How to optimize for inference a simple, saved TensorFlow 1.0.1 graph?
- Python decision tree visualization: a solution to graphviz’s executables not found
- No module named ‘sklearn.model_selection [How to Solve]
- Python Error – (sklearn) ImportError: No module named cross_validation
- Tensorflowcenter {typeerror} non hashable type: “numpy. Ndarray”