管道内决策树的可视化

Visualization of a decision tree inside a pipeline

我想用 export_graphviz 可视化我的决策树,但是我不断收到以下错误:


  File "C:\Users\User\AppData\Local\Continuum\anaconda3\envs\data_science\lib\site-packages\sklearn\utils\validation.py", line 951, in check_is_fitted
    raise NotFittedError(msg % {'name': type(estimator).__name__})

NotFittedError: This Pipeline instance is not fitted yet. Call 'fit' with appropriate arguments before using this method.

我非常确定我的管道已安装,因为我在我的代码中调用了 predict,它工作得很好。这是有问题的代码:

from sklearn.tree import DecisionTreeRegressor
import pandas as pd
import numpy as np
from sklearn.pipeline import Pipeline
from sklearn.model_selection import train_test_split
from sklearn.tree import export_graphviz

#Parameters for model building an reproducibility
state = 13

data_age.dropna(inplace=True)
X_age = data_age.iloc[:,0:77]
y_age =  data_age.iloc[:,77]

X = X_age
y = y_age

#split between testing and training set
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state= state)

# Pipeline with the regressor
regressors = [DecisionTreeRegressor(random_state = state)]
for reg in regressors:
    steps=[('regressor', reg)]
    pipeline = Pipeline(steps) #seed that controls the random grid search

#Train the model

pipeline.set_params(regressor__max_depth = 5, regressor__min_samples_split =5, regressor__min_samples_leaf = 5).fit(X_train, y_train)
pred = pipeline.predict(X_test)
pipeline.score(X_test, y_test)

export_graphviz(pipeline, out_file='tree.dot')

我知道我真的不需要这里的管道,但我仍然想了解问题是什么以供将来参考,并能够在已安装的管道内绘制决策树。

export_graphviz 的签名是 export_graphviz(decision_tree, ...) 可以在 documentation.

中看到

因此,您应该将决策树作为参数传递给 export_graphviz 函数而不是管道。

您还可以在 source code 中看到 export_grpahviz 正在调用 check_is_fitted(decision_tree, 'tree_') 方法。

因此,根据 Farseer 的回答,最后一行必须是:


#Train the model
pipeline.set_params(regressor__max_depth = 5, regressor__min_samples_split =5, regressor__min_samples_leaf = 5).fit(X_train, y_train)
pred = pipeline.predict(X_test)
pipeline.score(X_test, y_test)

#export as a .dot file
export_graphviz(regressors[0], out_file='tree.dot')

现在可以了。