(information gain) by default it is gini # model = tree.DecisionTreeRegressor() forregression# Train the model using the training sets andcheck score model.fit(X,y) model.score(X,y)#Predict predicted=model.predict(x_test) R code library(rpart) x # grow tree fit #Predict Output ...
https://machinelearningmastery.com/implement-decision-tree-algorithm-scratch-python/中给出了CART(Classification and Regression Trees,分类回归树算法,简称CART)算法的Python实现,采用的数据集为Banknote Dataset,这里在原作者的基础上,进行了略微改动,使其可以直接执行,code如下: 1. # reference: https://machinel...
plotTree.totalW = float(getNumLeafs(inTree)) #获取决策树叶结点数目 plotTree.totalD = float(getTreeDepth(inTree)) #获取决策树层数 plotTree.xOff = -0.5/plotTree.totalW; plotTree.yOff = 1.0; #x偏移 plotTree(inTree, (0.5,1.0), '') #绘制决策树 plt.show() 1. 2. 3. 4. 5. 6....
#build the tree recursively, the left and right tree are the "<" and ">" branch, respectively nodedict[cur_feaname]["<"] = buildtree(data_less,label_less) nodedict[cur_feaname][">"] = buildtree(data_greater,label_greater) returnnodedict #testcode: #mytree = buildtree(traindata,t...
Tree - Decision Tree with sklearn source code 决策树机器学习 After talking about Information theory, now let's come to one of its application - Decision Tree! Nowadays, in terms of prediction power, there are many ensemble methods based on tree that can beat Decision Tree generally. However ...
dt_model=DecisionTreeClassifier()# 训练模型 dt_model.fit(X_train,y_train)# 预测 y_pred=dt_model.predict(X_test)# 计算准确率 accuracy=accuracy_score(y_test,y_pred)print("Accuracy:",accuracy) 在上述代码中,我们使用了scikit-learn库中的DecisionTreeClassifier类来构建决策树模型,并使用鸢尾花数据集...
DecisionTree_python #coding:utf-8fromnumpyimport*frommathimport*importoperatordeffile2matrix(filename): fr=open(filename) lines=fr.readlines() lenth=len(lines) rematrix=zeros((lenth,7)) label=["seze","gendi","qiaoshen","wenli","qibu","chugan"]#西瓜特征集index=0forlineinlines:...
https://github.com/anlongstory/awsome-ML-DL-leaning/tree/master/lihang-reading_notes%20(with%20code)github.com/anlongstory/awsome-ML-DL-leaning/tree/master/lihang-reading_notes%20(with%20code) 5.决策树anlongstory/awsome-ML-DL-leaning5.决策树 决策树(decision tree)是一种基本的分类与回归...
CodeFolders and files Latest commit History17 Commits pic_results README.md dataset.jpg dataset.txt testdata.jpg testset.txt tree.py treePlotter.py 数据表.jpg 数据表.xlsx Repository files navigation README Decision_tree-python 决策树分类(ID3,C4.5,CART) 三种算法的区别如下: (1)...
A Decision tree is one of the easiest and most popular classification algorithms used to understand and interpret data. It can be utilized for both classification and regression problems. To easily run all the example code in this tutorial yourself, you can create a DataLab workbook for free ...