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learning-to-detect-motion-boundaries
- We propose a learning-based approach for motion boundary detection. Precise localization of motion boundaries is essential for the success of optical fl ow estimation, as motion boundaries correspond to discontinuities of the optical fl ow
slwgserver
- 森林王国库存版6603真正修复库存,随意更变前台库存,运营级别的服务端-Forest kingdom inventory version 6603 real repair inventory, random change more inventory inventory, operational level server
Stochastic_Bosque
- matlab 随机森林,可以直接使用,输入为特征矩阵,输出为目标值-Matlab random forest, can be used directly, the input feature matrix, the output value of the target
random-forest
- 基于随机森林的人脸识别,讲解详细,对初学者有很大的帮助- U57FA u4E8E u968F u673A u68EE u6797 u7684 u4EBA u8138 u8BC6 u522B uFF0C u8BB2 u89E3 u8BE6 u7EC6 uFF0C u5BF9 u521D u5B66 u8005 u6709 u5F88 u5927 u7684 u5E2E u52A9
20170106RF_Matlab
- 随机森林指的是利用多棵树对样本进行训练并预测的一种分类器,包括两个方面:数据的随机性选取,以及待选特征的随机选取。-Random forest refers to the use of more than one tree to sample the training and prediction of a classifier, including two aspects: random selection of data, as well as the characteristics of
cnmb
- 在本实验中,程序的输入是一个表示树结构的广义表。假设树的根为 root ,其子树森林 F = ( T1 , T2 , ... , Tn ),设与该树对应的广义表为 L ,则 L =(原子,子表 1 ,子表 2 , ... ,子表 n ),其中原子对应 root ,子表 i ( 1<i< n )对应 Ti 。例如:广义表 (a,(b,(c),(d)),(f,(g),(h ),(i))) 表示的树如图所示: 程序的输出为树的层次结构、树的度以及各种度的结点个数。
cases-for-R
- R的一些案例,包括随机森林、支持向量机、神经网络、决策树、判别分析-some cases of randaom forest,SVM,ANN,decision trees and discriminant analisis for R
Ensemble-Learning
- 集成学习将若干基分类器的预测结果进行综合,具体包括Bagging算法和AdaBoost算法;还有随机森林算法,利用多棵树对样本进行训练并预测的一种分类器-Integrated learning integrates the prediction results of several base classifiers, including Bagging algorithm and AdaBoost algorithm and random forest algorithm, using a t
erleidiaocha
- 林业二类调查制表程序,行业应用系统开发例子。-Forest Inventory for Planning and tabulation procedures, industry application development examples.
exampleRF
- 随机森林在MATLAB上的实现,并且可以对特征进行重要性排序选择。-Random Forest on MATLAB implementation, and can characteristics in order of importance.
improve_rotation_forest
- 改进的旋转森林代码,直接可以在matlab上运行-Improved rotary forest code that can be run directly on matlab
cjfzhgj
- 词林在线词典汉字简体-繁体互相转换输入工具,包含完整的简繁对应词典库,输入你要查询的简体字,点击转换按钮,就能转换为繁体字。 源码含javascr ipt和PHP两种,修改后可以快速使用。-The word forest online dictionary Chinese characters simplified- traditional conversion input tools, including complete corresponding simplified dictiona
fire-fujian
- 模拟森林火灾,元胞有三个状态,0是空位,1是燃烧的树,2是树木。如果4个邻居中有一个或者一个以上的是燃烧着的并且自身是树木,那么该元胞下一时刻的状态是燃烧。-Simulated forest fire, the cell has three states, 0 is the space, 1 is the burning tree, 2 is the tree. If one or more of the four neighbors are burning and are themselves
RandomForest
- 机器学习随机森林源码。改变决策树的深度对比分类结果。对鸢尾花数据进行决策树分析-random forest
Forest
- COMPRESSIVE SENSING ALGORITHM
several-classification-algorithm
- 几种基于Matlab的分类算法研究(自组织神经网络,SOM神经网络,LVQ神经网络,决策树,随机森林算法)-Several classification algorithm based on Matlab research (self-organizing neural network, SOM neural network and LVQ neural network, decision tree, the random forest algorithm)
gcforest
- 周志华教授深度森林算法代码,用于分类精度接近深度学习算法-Professor zhihua s deep forest algorithm code is used to classify precision approach to deep learning algorithm
randomForest_4.6-12.tar
- 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
最后
- 第一题:将一颗树或森林转换为二叉树 第二题:求森林高度 第三题:按层次方式遍历森林 第四题:输出一个森林中每个结点的值及对应的层次数 第五题:输出一个森林的广义表形式(First question: convert a tree or forest into two branches Second question: forest height The third question: traverse the forest in a hierarchical manner The
assignment(1 ) SIS_NBNN
- 运用SIS+NBNN的方法进行分类,运用参考文献里的有关SIS与NBNN相结合的知识,所提供的两类数据,按照注意里的相关事项完成“bedroom”“forest”的分类。(The use of SIS+NBNN methods for classification, the use of reference in the SIS and NBNN combination of knowledge, provided by the two types of data, according to t