搜索资源列表
Random_Forest_fortran
- 加洲大学Leo Breiman编写的Random Forests(随机器森林)各个版本的fortran代码 可以实现分类,以及回归!-University of California Leo Breiman prepared by Random Forests (random for forest ) fortran various versions of the code can be achieved classification and regression!
RandomForests_paper
- 介绍随机森林(Random Forest)最早的,最经典文献!LEO BREIMAN.Random Forests.Machine Learning, 45, 5–32, 2001-introduced random forests (Random Forest) the earliest, The most classic literature! LEO Le BREIMAN.Random Forests.Machine Jiaotong, 45, 5-32, 2001
RandomForestCversion
- 组合学习算法的新方法--随机森林(Random Forest,RF),用于处理高维问题,可以得到满意的效果!-composition of the new learning algorithm methods -- random forests (Random Forest, RF) for the treatment of high-dimensional problem, it can be satisfied with the results!
Windows-Precompiled-RF
- matlab 的随机森林代码,很不错,学习rf必备-matlab code for random forests, very good
random-forest
- 随机森林算法是opencv中的重要的算法,其中讲述了随机森林的定义特征构建方法等-Random Forests algorithm is an important algorithm in opencv, which describes the defining characteristics of a random forest construction methods
RF_MexStandalone-v0[1].02
- 随机森林算法 C++和matlab程序结合-Random forests algorithm C++ and matlab program combines
RF
- Random Forests的Fortran版本,Leo Breiman and Adele Cutler 设计-Random Forests of the Fortran version, Leo Breiman and Adele Cutler Design
89346509RandomForestMatlabVersion
- 這是一個 Matlab的(和獨立應用)端口的出色的機器學習算法,隨機森林` - 由Leo布賴曼等。從 R -源由Andy鴻等。 http://cran.r-project.org/web/packages/randomForest/index.html(Fortran的原由Leo布賴曼和Adele卡特勒,研究港口安迪鴻和馬修維納。)當前的代碼版本是基於 4.5-29從來源 randomForest包。-This is a Matlab (and Standalone application) p
RandomForests
- 关于机器学习领域分类的随机森林算法的相关学习资料-learning things about random forests
Bagging_predictors
- 介绍Bagging最早的、最经典的文献,作者是Bagging和随机森林的创始人LEO BREIMAN-Bagging first introduced, the most classic literature, the author is the founder of Bagging and random forests LEO BREIMAN
SINISAS-HOME-PAGE.files
- The learning process involves three steps: (a) learning the random forests, (b) constructing the second-level training set, and (c) learning the stacked classifier.
Random-Forest-for-Image-Annotation
- 随机森林算法,适合初学者阅读,包括公式,资料,调试-Random forests algorithm, suitable for beginners to read, including formulas, data, commissioning
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-forests
- 用openCV写的一个能实现随机森林算法的程序,大家可以参考一下-OpenCV written by a Random Forest algorithm to achieve the procedure, we can refer to
random-forests
- 基于随机森林的烤烟香型分类研究,很好的将烤烟香型分类与随机森林算法结合在一起。-Classification of Tobacco flavor random forest, a good flavor of the flue-cured tobacco in conjunction with the random forest classification algorithm together.
online-random-forests-master
- 在线随机森林算法的源码,用于分类模式识别有很好的效果,适用于linux系统下。-Online Random Forest algorithm source code, for classification pattern recognition have a good effect for linux system.
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
- 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
bagging-boosting-random-forests-master
- bagging 工具箱,随机森林工具箱,使用MATLAB2014b 环境测试(Bagging toolbox, random forest toolbox, using the MATLAB2014b test environment)
Random-Forests-Matlab-master (2)
- 要说随机森林,必须先讲决策树。决策树是一种基本的分类器,一般是将特征分为两类(决策树也可以用来回归,不过本文中暂且不表)。构建好的决策树呈树形结构,可以认为是if-then规则的集合,主要优点是模型具有可读性,分类速度快。(In machine learning, a random forest is a classifier that contains multiple decision trees, and its output category is determined by the m