개요
- skleran.tree.plot_tree의 색상을 바꿔보도록 한다.
- matplotlib 객체지향의 구조를 알면 어렵지(?) 않게 바꿀 수 있다.
- 간단하게 plot_tree 시각화를 구현해본다.
- 언제나 예제로 희생당하는 iris 데이터에게 애도를 표한다.
- 구글코랩에서 실행 시, 다음 코드를 실행하여 최신 라이브러리로 업그레이드 한다.
!pip install -U matplotlib
Requirement already satisfied: matplotlib in /usr/local/lib/python3.7/dist-packages (3.2.2)
Collecting matplotlib
Downloading matplotlib-3.5.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (11.2 MB)
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Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.7/dist-packages (from matplotlib) (7.1.2)
Requirement already satisfied: pyparsing>=2.2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib) (3.0.7)
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Collecting fonttools>=4.22.0
Downloading fonttools-4.31.2-py3-none-any.whl (899 kB)
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Installing collected packages: fonttools, matplotlib
Attempting uninstall: matplotlib
Found existing installation: matplotlib 3.2.2
Uninstalling matplotlib-3.2.2:
Successfully uninstalled matplotlib-3.2.2
[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.[0m
Successfully installed fonttools-4.31.2 matplotlib-3.5.1
%matplotlib inline
import sklearn
print(sklearn.__version__)
import matplotlib
print(matplotlib.__version__)
# 필수 라이브러리 불러오기
from sklearn.datasets import load_iris
from sklearn import tree
import matplotlib.pyplot as plt
# 데이터 불러오기
iris = load_iris()
print(iris.data.shape, iris.target.shape)
print("feature names", iris.feature_names)
print("class names", iris.target_names)
# 모형 학습 및 plot_tree 그래프 구현
dt = tree.DecisionTreeClassifier(random_state=0)
dt.fit(iris.data, iris.target)
fig, ax = plt.subplots(figsize=(10, 6))
ax = tree.plot_tree(dt, max_depth = 2, filled=True, feature_names = iris.feature_names, class_names = iris.target_names)
plt.show()
1.0.2
3.5.1
(150, 4) (150,)
feature names ['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)']
class names ['setosa' 'versicolor' 'virginica']
