搜索资源列表
RF_MexStandalone-v0.02
- random forest
src.tar
- These are random forest implementations for various multi-class machine learning tasks.
matlab-RandomForests
- matlab编写的随机森林算法，别人编写的，分享一下-Random Forest algorithm matlab prepared, written by someone else, share
randomForest_4.6-7
- Random Forest brain tumor segmentation
randomforest-matlab
- Random Forest可以运行的代码。从csdn上面当下来的。-Random Forest Source Code
TextDetect
- 该代码利用canny算子实现了文字检测，还使用了随机森林算法，运用了boost库和opencv库，检测效果非常好，平台是Visual Studio 2010-The code implements the use of canny operator Text Detection, also used the random forest algorithms use the boost libraries and opencv library, testing the effect is very
Random-Forest-Matlab-master
- This toolbox was written for my own education and to give me a chance to explore the models a bit. It is NOT intended for any serious applications and it does not NOT do many of things you would want a mature implementation to do, like leaf pruni
randomforesttt
- 随机森林分类器，matlab写的，直接可以运行，不需要该任何东西-Random Forest classifier, matlab write, direct run, does not require that anything
Random-Forest(R)
- 随机森林使用R语言实现（包括各种参数的分析介绍）-Random forests using R language implementation (including the analysis of the various parameters)
Random-Forest
- 有关随机森林的代码和源文件，代码需要使用使用fortran来搭配，自己配吧-About the random forest code and source files
RF_Class_C
- 随机森林训练测试模型，用于特征的分类与测试-Random Forest model training tests
RF_Reg_C
- 随机森林训练测试模型，用于矩阵的线性回归算法-Random Forest model training tests
randomforest-matlab
- random forest matlab code
random-forest-example
- 随机森林是用随机的方式建立一个森林，森林里面有很多的决策树组成，随机森林的每一棵决策树之间是没有关联的。在得到森林之后，当有一个新的输入样本进入的时候，就让森林中的每一棵决策树分别进行一下判断，看看这个样本应该属于哪一类，然后看看哪一类被选择最多，就预测这个样本为那一类。-Random forests are used in a random way to build a forest, there are a lot of decision trees in the forest, there
Random-Forest-Matlab-master
- 随机森林的matlab实现，即随机森林算法的matlab工具箱，从GitHub上获取，使用请注明出处。(random forest for matlab)
forest
- an enhance algoritm of random forest
Random Forest
- 利用随机森林训练，对polar码进行解码(The polar code is decoded by random forest)
Random Forest
- 在机器学习中，随机森林是一个包含多个决策树的分类器， 并且其输出的类别是由个别树输出的类别的众数而定。 Leo Breiman和Adele Cutler发展出推论出随机森林的算法。 而 "Random Forests" 是他们的商标。 这个术语是1995年由贝尔实验室的Tin Kam Ho所提出的随机决策森林（random decision forests）而来的。这个方法则是结合 Breimans 的 "Bootstrap aggregating" 想法
randomforest.R
- R 语言 随机森林分类特征选择，打分特征重要性(R language random forest feature selection importance)
random forest-matlab
- random forest-matlab随机森林matlab实现