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高风代码
- 本内容是有关机器学习的包含贝叶斯分类器，随机森林，支持向量机，神经网络，logistic多元回归等(The contents of this paper are machine learning, including Bayesian classifier, random forest, support vector machines, neural network, logistic multiple regression and so on)
[www.17zixueba.com]10.RandomForest代码
- 随机森林代码 通过Python来实现的，效果还不错~~~(Random forest code through Python to achieve, the effect is not bad ~!)
RF_Reg_C
- 随机森林实现分类、预测的代码和一些相应的实例，啊啊啊啊啊(Random forest classification, prediction of the code and some corresponding examples, ah, ah, ah!)
rfuncs
- 用随机森林的方法进行特征选择，对200了影像特征数据进行分类(Feature selection using random forest methods)
RF_MexStandalone-v0.02-precompiled
- 随机森林工具包可以直接用来分类和回归，大家一起探讨和学习(Random forest toolkit can be directly used for classification and regression, we explore and study together)
各种分类器matlab程序
- 里面有随机森林，C4.5，ID3，SVM等分类器的matlab代码(There are random forest, C4.5, ID3, SVM classifiers matlab code)
randomforest-matlab
- 基于c运行库的matlab随机森林工具箱，特点运行快(Matlab random forest toolbox based on C runtime library features fast operation)
随机森林
- 作为新兴起的、高度灵活的一种机器学习算法，随机森林（Random Forest，简称RF）拥有广泛的应用前景，从市场营销到医疗保健保险，既可以用来做市场营销模拟的建模，统计客户来源，保留和流失，也可用来预测疾病的风险和病患者的易感性。(As a new, highly flexible a machine learning algorithm, random forest (Random Forest, referred to as RF) has broad application prosp
codes
- MATLAB实现随机森林，代码包放入toolbox文件夹，添加进matlab，自带数据，可以直接执行。(Achieve random forest based on MATLAB, a code package needs to put into the toolbox folder, add to the MATLAB by setting path. IT can be directly implemented with the data.)
Class_8
- 介绍决策树与随机森林算法的定义及应用，包含matlab程序(This paper introduces the definition and application of decision tree and random forest algorithm, including Matlab program)
MC
- 大数据挖掘，随机森林算法，可用于分类，特征向量选择等等。(random forest ,data minning)
RF_Class_C
- matlab 随机森林 机器学习 二类分类器(matlab random forest)
gcforest
- 使用深度随机森林实现对数据的分类，无论数据特征是数值型的还是符号型的。(Using a deep random forest to implement the classification of data, whether the data features are numerical or symbolic.)
特征提取程序
- 特征提取，随机森林实现特征重要性排序，用python实现(Feature extraction and classification of characteristic importance in random forest)
Iris_RandomForest
- python鸢尾花（iris）数据分类程序举例，采用随机森林算法。(Python iris flower (IRIS) data classification program is used for example, and the random forest algorithm is used.)
stacking
- kaggle digitrecognizer MNIST by stacking some machine learning method, such like GBM(Gradient Boosting Method), LR, Extra Randomized Trees, Random Forest,KNN,etc.用stacking的方法实现手写数字识别MNIST。(kaggle digitrecognizer MNIST by stacking some machine learnin
机器学习常用方法
- 机器学习常用方法的python实现，包括PCA，随机森林，决策树，层次聚类，kmeans，KNN，线性感知机等(Python implementation of common machine learning methods, including PCA, random forest, decision tree, hierarchical clustering, kmeans, KNN, linear perceptron, etc.)
决策树与随机森林
- 给出对决策树与随机森林的认识。主要分析决策树的学习算法：信息增益和ID3、C4.5、CART树，然后给出随机森林。 决策树中，最重要的问题有3个: 1. 特征选择。即选择哪个特征作为某个节点的分类特征； 2. 特征值的选择。即选择好特征后怎么划分子树； 3. 决策树出现过拟合怎么办？ 下面分别就以上问题对决策树给出解释。决策树往往是递归的选择最优特征，并根据该特征对训练数据进行分割。(The understanding of decision tree and random
RF_Class_C
- 在matlab中，运用随机森林算法来解决图像特征处理的问题。(In Matlab,the random forest method is used to solve the classification of image features.)
SVM_Mdl.mat
- These files are matlab source code for price forecasting for smart meter hourly data. Step 1 relevant features are selected by Gray Correlation, Random Forest, Relief F algorithms. Then Kernel PCA of features are calculated. Price is predicted by Ker