1>>>importtrees2>>>reload(trees)3<module'trees'from'E:\python excise\trees.pyc'>4>>> myDat,labels=trees.createDataSet()5>>>myDat6[[1, 1,'yes'], [1, 1,'yes'], [0, 1,'no'], [0, 1,'no'], [0, 1,'no']]7>>>trees.calc
2. Sources: (a) Cendrowska, J. "PRISM: An algorithm for inducing modular rules", International Journal of Man-Machine Studies, 1987, 27, 349-370 (b) Donor: Benoit Julien (Julien@ce.cmu.edu) (c) Date: 1 August 1990 3. Past Usage: 1. See above. 2. Witten, I. H. & MacDonal...
knn = neighbors.KNeighborsClassifier(algorithm = 'auto',leaf_size = 30,n_neighbors=3,warn_on_equidistant = True,weights = 'uniform') 10. knn.fit(trainImage,trainLabel) 11. match = 0; 12. for i in xrange(len(testLabel)): 13. 0] 14. print i,' ', 15. print predictLabel,' ',...
https://github.com/DianeSoHungry/ShallowMachineLearningCodeItOut/blob/master/ID3.ipynb 现在要介绍的是ID3决策树算法,只适用于标称型数据,不适用于数值型数据。 决策树学习算法最大的优点是,他可以自学习,在学习过程中,不需要使用者了解过多的背景知识、领域知识,只需要对训练实例进行较好的标注就可以自学习了。
Ruleset 是一个用 2/3 训练数据训练 ID3Tree 的类,并将其转换为一组规则,然后用剩下的 1/3 数据(以 C4.5 的方式,https://en.wikipedia.org/wiki/C4.5_algorithm)修剪规则。 Bagging 是一个基于 Bagging 的训练器,它可以训练 10 个 Ruleset 训练器,并通过投票预测最佳的输出结果。 详细信息请访问以下链接...
http://archive.ics.uci.edu/ml/machine-learning-databases/lenses/ 1. 数据描述信息: 1. Title: Database for fitting contact lenses 2. Sources: (a) Cendrowska, J. "PRISM: An algorithm for inducing modular rules", International Journal of Man-Machine Studies, 1987, 27, 349-370 ...
The Modified ID3 algorithm is implemented in python programming by using a reduced feature set of the Hepatitis C virus dataset (Hoffmann et al. in J Lab Precis Med 3:58, 2018) along with standard ML algorithms, such as ID3, support vector machine, random forest, and other recent states ...
ID3 Decision Tree Algorithm 介绍一下ID3 决策树算法 变量介绍 对于一个多分类问题我们通常将数据集$D$分为训练集$D_{train}$和测试集$D_{test}$。对于数据集$D$上每个数据$d$都有$k$个属性${a_1,a_2,…,a_k}$,每个属性都有一个明确的输出$output$,全部分类数的个数计做$y$。 生成决策树 ...
/usr/bin/python# -*- coding:utf-8 -*-""" Re-implement ID3 algorithm as a practice Only information gain criterion supplied in our DT algorithm. 使用该 ID3 re-implement 的前提: 1. train data 的标签必须转成0,1,2,...的形式 2. 只能处理连续特征...
1. The information theory basis of decision tree ID3 algorithm The machine learning algorithm is very old. As a code farmer, I often knock on if, else if, else, but I already use the idea of decision tree. Just have you thought about it, there are so many conditions, which co...