搜索资源列表
c4.5r8sourcecode
- c4.5的源码决策树最全面最经典的版本-Bank of the most comprehensive source of decision tree of the most classic version
C4.5文档说明
- C4.5文档说明（数据类型，运行环境）-The explain of C4.5 document(data type,run environment)
Efficient C4.5
- Efficient C4.5
C4.5算法源程序
- C4.5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。-C4.5 decision tree algorithms to generate information gain the greatest attribute as a classification attributes, generate decision tree, and came to decision-making rules.
c4.5算法数据(VC VERSION)
- 数据挖掘c4.5算法（vc语言版本）欢迎大家下载测试！！！！ - The data mining c4.5 algorithm (vc language edition) welcome everybody downloading test! ! ! !
c4.5_www2.cs.uregina.ca
- 来自于www2.cs.uregina.ca的c4.5源码-from the Bank www2.cs.uregina.ca FOSS
C4.5算法
- 数据挖掘中的决策树C4.5算法的实现,用matlab实现-Data Mining Decision Tree Algorithm of C4.5, using Matlab to achieve
c4.5ID3javasharepacket
- c4.5 ID3 分类决策数 公用java包 share-Bank classification decisions ID3 few packets share common java
C4.5java
- 这是决策树C4.5算法的java版源码。希望大家能喜欢，愿共同分享！-Decision Tree Algorithm C4.5 java version of the source code. Hope you will like it is willing to share!
c4[1].5r8
- 用于数据挖掘的分类算法,基于c语言的,一个c4.5分类算法-used for the classification of data mining algorithms, based on the c language, a classification algorithm c4.5
C4.5-C
- 这是数据挖掘分类算法中的C4.5算法的C实现版本，为Linux下的，希望对大家有所帮助。-This is the classification of data mining algorithms to the C4.5 algorithm to achieve the C version of Linux. We want to help.
c4-5
- c4.5主要函数的matlab实现，简单易懂，扩展性很强-c4.5 main function of the Implementation of Matlab, simple, strong expansion
C4.5_Kidney
- 以从医院病案室获得的3022例数据为样本，在完成样本数据库以及糖尿病并发症的多维数据集设计后，以糖尿病并发症流行病学知识发现为重点，研究定性数据定量化挖掘模型及算法引擎的设计与实现，即将关联模型引入糖尿病并发症的流行病学研究.运用决策树技术对数据样本进行分析，采用C4.5找到最优决策树-cases from the hospital to obtain the data for 3,022 cases samples the compl
ID3+C4.5
- ID3+C4.5的源程序。用于数据挖掘决策算法的一个实例。-ID3 C4.5 of the source. Data Mining for a decision algorithm examples.
c4.5
- 数据挖掘算法中，有关决策树算法c4.5的实现，c4.5是在ID3基础上实现的，有这比id3还好的功能-Data mining algorithms, the decision tree algorithm c4.5 realization, c4.5 is based on ID3, with this function better than id3
C4.5
- 决策树是表达知识的一种有效形式，这个是挖掘决策树的经典c4.5算法-Decision tree is to express an effective form of knowledge, this is a classic mining decision tree algorithm c4.5
C4.5
- C4.5算法有如下优点：产生的分类规则易于理解，准确率较高。其缺点是：在构造树的过程中，需要对数据集进行多次的顺序扫描和排序，因而导致算法的低效。此外，C4.5只适合于能够驻留于内存的数据集，当训练集大得无法在内存容纳时程序无法运行。-C4.5 algorithm has the following advantages: the classification rules easier to understand, accurate a
c4.5
- C4.5决策树算法，使用VC++实现的，比较好用 -C4.5 decision tree algorithm, use VC++ Realize relatively easy to use
C4.5-2
- 数据挖掘中的c4.5算法 给予决策树-Data Mining in the given decision tree algorithm c4.5
c4.5
- 通过C4.5 的实现可以进行构建决策树 来进行有效的分类-Through the realization of C4.5 decision tree can be constructed to carry out an effective classification