from sklearn.datasets import load_iris import matplotlib.pyplot as plt # load data X, y = load_iris(return_X_y=True) # create and train model clf = tree.DecisionTreeClassifier(max_depth=4) # set hyperparameter clf.fit(X, y) # plot tree plt.figure(figsize=(12,12)) # set plot si...
本文简要介绍python语言中sklearn.tree.plot_tree的用法。 用法: sklearn.tree.plot_tree(decision_tree, *, max_depth=None, feature_names=None, class_names=None, label='all', filled=False, impurity=True, node_ids=False, proportion=False, rounded=False, precision=3, ax=None, fontsize=None) 绘...
完整代码示例 fromsklearn.datasetsimportload_irisfromsklearn.treeimportDecisionTreeClassifierfromsklearn.treeimportplot_treeimportmatplotlib.pyplotasplt# 准备数据集iris=load_iris()X=iris.data y=iris.target# 构建决策树模型clf=DecisionTreeClassifier()clf.fit(X,y)# 绘制决策树fig,ax=plt.subplots(figsize=...
# import dtreeplot package model_plot functionfromdtreeplotimportmodel_plotfromsklearnimportdatasetsfromsklearn.treeimportDecisionTreeClassifieriris=datasets.load_iris()X=iris.datay=iris.targetfeatures=iris.feature_namesclf=DecisionTreeClassifier(max_depth=3,random_state=1234)model=clf.fit(X,y)# visuali...
接下来,我们将使用plot_tree函数来可视化决策树模型。代码如下: fromsklearn.treeimportplot_treeimportmatplotlib.pyplotasplt plt.figure(figsize=(20,10))plot_tree(clf,feature_names=iris.feature_names,class_names=iris.target_names,filled=True)plt.savefig('decision_tree.png')plt.show() ...
This means you want to look at the decision boundaries of the tree. Fortunately, Scikit-Learn already has a DecisionBoundaryDisplay in the sklearn.inspection module. First, we'll load a toy wine dataset and divide it into train and test sets: from sklearn.datasets import load_wine from sk...
经查验参考资料，sklearn并非使用了课上以及书上讲的ID3算法，而是选择了CART，该算法生成二叉树；scikit...
python from sklearn.datasets import load_iris from sklearn import tree # 加载数据集 iris = load_iris() X, y = iris.data, iris.target # 训练决策树模型 clf = tree.DecisionTreeClassifier(random_state=0) clf = clf.fit(X, y) 3. 使用 plot_tree 函数绘制决策树 在准备好数据集和决策树模...
问决策树AttributeError: Jupyter Notebook中的模块'sklearn.tree‘没有属性'plot_tree’错误ENPython语言...
from sklearn.datasets import load_iris将鸢尾花资料库存入,iris为一个dict型别资料。 每笔资料中有4个特征,一次取2个特征,共有6种排列方式。 X (特征资料) 以及 y (目标资料)。 DecisionTreeClassifier建立决策树分类器。 importnumpyasnp importmatplotlib.pyplotasplt ...