搜索资源列表
C4-3
- 对于一元二次方程ax^2 + bx + c 0,解可以分为很多情况。 若该方程有两个不相等实根，首先输出1，换行，然后从小到大输出两个实根，换行； 若该方程有两个相等实根，首先输出2，换行，然后输出这个这个实根，换行； 若该方程有一对共轭复根，输出3，换行； 若该方程有无解，输出4，换行； 若该方程有无穷个解，输出5，换行； 若该方程只有一个根，首先输出6，换行，然后输出这个跟，换行；-For a quadratic equation
DT
- 人工智能方面的决策树算法，包括C4.5 ID3 CART三种评判标准实现方式 -Artificial intelligence decision tree algorithms, including three kinds of criteria C4.5 ID3 CART implementation
KCB-AKHR
- Kecerdasan buatan decision tree untuk menentukan masa studi mahasiswa menggunakan algoritma c4.5
Decision-tree-algorithm
- 数据挖掘，机器学习经典分类算法,决策树算法ID3 C4.5 Java实现 开发环境 eclipse-Data mining, machine learning classic classification algorithm, decision tree algorithm ID3 C4.5 Java development environment eclipse
BreastCancer
- Code for Classification Accuracy of KNN, C4.5 and SVM algo in R
LZOLJWB
- c4,5主要函数的matlab实现,简单易懂,扩展性很强,很好的-C4, five major functions of matlab, easy to understand, scalability is very strong, very good
splrdter
- c4,5主要函数的matlab实现,简单易懂,扩展性很强,很好的-C4, five major functions of matlab, easy to understand, scalability is very strong, very good
hlgorithms
- 数据挖掘算法,分类树的C4,5算法,用于模式分类,不错的-Data mining algorithms, classification tree C4, 5 algorithm, used for pattern classification, pretty good
cujsorbynaheticvowel
- c4,5主要函数的matlab实现,简单易懂,扩展性很强,很好的-C4, five major functions of matlab, easy to understand, scalability is very strong, very good
KJTOPT79
- 数据挖掘算法,分类树的C4,5算法,用于模式分类,不错的-Data mining algorithms, classification tree C4, 5 algorithm, used for pattern classification, pretty good
C45algorithm-master
- C4.5 algorithm implementation source code, developed by Ross Quinlain which classifies data, using decision trees.
680518
- c4,5主要函数的matlab实现,简单易懂,扩展性很强,很好的(C4, five major functions of matlab, easy to understand, scalability is very strong, very good)
决策树（java）variance 回归
- mllib调用决策树的java代码，希望对大家有帮助(Mllib calls the Java code of the decision tree)
iegorithms-pretty
- 数据挖掘算法,分类树的C4,5算法,用于模式分类,不错的(Data mining algorithms, classification tree C4, 5 algorithm, used for pattern classification, pretty good)
决策树C4.5
- 利用决策树训练训练器 分辨 有毒蘑菇和无毒蘑菇 java书写，包含训练集及说明 代码无bug(Using decision tree training trainer to distinguish poisonous mushroom and non-toxic mushroom Java writing, including training set and explanation code.)
src
- Java Source Code for Decision Tree C4.5
排序和机器学习常见算法
- 数据结构（排序）、机器学习（聚类、相似性、C4.5）常用算法总结(Summary of data structure and machine learning algorithms)
weka机器学习十大算法
- 对机器学习领域的十个经典算法进行了详细介绍，包括：AdaBoost、Apriori、C4.5、CART、EM、K-means、kNN、PageRand、SVM和朴素贝叶斯(Ten classical algorithms in machine learning domain are introduced in detail, including AdaBoost, Apriori, C4.5, CART, EM, K-means, kNN, PageRand, SVM and Nave Baye
6475607
- 决策树算法C4 5源码, The directory Data contains some sample datasets M()
random forest-matlab
- rf-随机森林：一个简单的随机森林例子，包含C4.5，ID3等多种信息熵计算过程(A simple example of random forest, including C4.5, ID3 and other information entropy calculation process)