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c4.5java
- 决策树分类算法，c4.5，java语言进行描述的-Decision tree classification algorithm, c4.5, java language described
1
- D3的源码决策树最全面最经典的版本.id3决策树的实现及其测试数据.id3 一个有用的数据挖掘算法，想必对大家会有所帮助！id3算法进行决策树生成 以信息增益最大的属性作为分类属性，生成决策树，从而得出决策规则。-D3 of the source tree the most comprehensive version of the most classic. Id3 decision tree and its test data. Id3 a useful data mining algorit
CART
- 此为机器学习算法中的决策树方法之一CART，也是决策树的基本算法-This is the machine learning algorithm, one of the decision tree method CART, is the basic decision tree algorithm
GA_SVM
- 对于小样本而言，SVM的仿真效果要比神经网络好，但是SVM的性能依赖于它的两个训练参数，本算法是用GA自动选择SVM的两个参数。-For small sample case, SVM simulation results than the neural network is good, but the performance of SVM depends on its two training parameters, the algorithm is automatically selected
decisiontree
- 决策树算法程序，用于分类 使用的数据集为合成标签数据集-failed to translate
Watermelon
- 通过ID3决策树算法训练决策树规则，对西瓜的好坏进行判别(hrough the ID3 algorithm to determine the quality of watermelon)
C4_5
- C4.5算法，优秀的决策树算法，由于求解特征分类问题(C4.5 algorithm, an excellent decision tree algorithm, especially for the problem of feature classification)
C4_5
- 决策树分类算法C4.5的matlab代码实现，可返回训练集和测试集的结果，有详细注释(classification tree)
决策树
- 决策树id3算法matlab代码，已调试，根据需要改写main函数，实现数据分类功能(code for decision tree)
pres
- 三种分类器：决策树分类器，k-NN分类器和k-means分类器的运行时间以及运行准确率的比较。(Three kinds of classifiers: decision tree classifier, k-NN classifier and K-means classifier running time and accuracy comparison.)
chapter28
- 机器学习的决策树问题算法matlab实现，有注释和源码(Machine learning decision tree algorithm matlab implementation, with notes and source code)
Class_8
- 介绍决策树与随机森林算法的定义及应用，包含matlab程序(This paper introduces the definition and application of decision tree and random forest algorithm, including Matlab program)
CART
- 决策树CART算法源代码，可利用，包括make_tree和use_tree(the code of decision tree CART algorithm including make_tree and use_tree)
ID3决策树
- Java实现用ID3算法构建决策树(Java implementation using ID3 algorithm to build decision tree)
treePlotter
- 绘制ID3，C4.5,CRAT决策树算法的树型(Drawing the tree pattern of ID3, C4.5, CRAT decision tree algorithm)
DT
- 调用于sklearn平台的决策树算法，有着较好的分类能力(The decision tree algorithm used in sklearn platform has good classification ability)
GBDT
- 调用于sklearn平台的梯度提升决策树算法，有着较好的分类能力(The GBDT algorithm used in sklearn platform has good classification ability)
ID3
- 基于matlab的决策树ID3算法，完成对数据集的分类问题(Based on matlab decision tree ID3 algorithm, the classification of data sets is completed.)
MATLAB
- 本书论述在MATLAB环境下如何实现神经网络，包括了常用的神经网络及相关理论，如BP神经 网络、RBF神经网络、SVM、SOM神经网络、灰色神经网络、决策树、随机森林、小波神经网络、NARX神经网络等以及各种优化算法与神经网络的结合。((This book discusses how to realize neural network in MATLAB environment, including the commonly used neural network and related the
C4.5
- 使用matlab实现C4.5决策树算法核心(Implementing the Core of C4.5 Decision Tree Algorithms with MATLAB)