搜索资源列表
random-forest
- 决策树模型的C++实现,可用来组成随机森林建立随机森林分类器做数据分类及图像分类,代码中有简单的测试样例-C++ implementation of decision tree model, to form a random forest is used to establish the random forest classifier for data classification and image classification, the code is simple test sample
DM6_decision_tree
- 实现ID3决策树算法,可以实现基本眜分类,最终的决策树是以结构体存放的-ID3 decision tree
RuleGen_v1[1].02
- 一款实用的envi决策树编码程序,能快速有效对影像分类-A practical envi tree coding procedures
crf_trees.v0.11
- 决策树源代码,用matlab语言编写的,适用于分类及相关问题的分析-Decision tree source code, written with matlab language, suitable for classification and analysis of the related problem
c4.5
- C4.5是机器学习算法中的另一个分类决策树算法,它是基于ID3算法进行改进后的一种重要算法,相比于ID3算法,改进有如下几个要点:用信息增益率来选择属性.-C4.5 decision tree algorithm is another classification machine learning algorithm, which is based on ID3 algorithm is an important algorithm improved, compared to the ID3 a
bayes
- 贝叶斯分类算法是统计学的一种分类方法,它是一类利用概率统计知识进行分类的算法。在许多场合,朴素贝叶斯(Naï ve Bayes,NB)分类算法可以与决策树和神经网络分类算法相媲美.- Bayesian classification algorithm is a statistical classification method, which is a kind of knowledge to classify the use of probabilistic algorithms.
lenses
- 通过Python语言来创建决策树,并且用决策树来进行隐形眼镜的分类。-Python language by creating a decision tree and decision tree classification for contact lenses.
ensemble-learing-for-decision-tree
- 决策树的集成学习,用Java语言实现!具有良好的分类性能!-ensemble learning for decision tree
ID3-tree
- ID3决策树算法,可以使用决策树对数据集分类,并且生成最好的决策树,并且可以输出决策树。-ID3 decision tree algorithm, you can use the decision tree classification data sets, and generate the best decision tree, and the tree can be output.
jueceshu
- 决策树算法,根据已建立的知识库,对用户的输入进行分类。-jue ce shu algorithm,we can use it to get the kind of user s input,according the knowledge in the store.
Bayes
- 贝叶斯分类算法是统计学的一种分类方法,它是一类利用概率统计知识进行分类的算法。在许多场合,朴素贝叶斯(Naï ve Bayes,NB)分类算法可以与决策树和神经网络分类算法相媲美,该算法能运用到大型数据库中,而且方法简单、分类准确率高、速度快。-Bayesian classification algorithm is a statistical classification method, which is a kind of knowledge to classify the use
C4.5
- 数据挖掘分类算法决策树C4.5数据挖掘分类算法决策树C4.5-data mining C4.5
RandomForest_matlab
- 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-Random Forest is a decision tree classifier comprising a plurality, and its output is the category number by individual trees all output categories may be
binary_decision_tree_v1.0
- 实现图像分类,基于二元决策树模型,代码通俗易懂-Realization of image classification, based on the binary decision tree model straightaway code
ID3
- 用于决策树中对数据进行分类,适合机器学习等领域-For a decision tree to classify data for machine learning and other fields
DecisionTree
- matlab代码实现决策树,是学习数据挖掘的基本分类器的入门代码-DecisionTree classifier about data mining coded by matlab
RandomForestaAdaBoost
- 随机森林,决策树以及adaboost分类器的java实现。随机森林和adaboost都基于决策树完成。-Random forests, tree and adaboost classifier java. Random Forest and adaboost are based on the decision tree is complete.
syn_13
- 以网格采样方法构建训练集,训练决策树,对图像分类。-Grid sampling method for constructing the training set, training the decision tree, for image classification.
wuge
- id3决策树 5个代码的实现 可以实现信息熵的计算 和 分类准则-This course shows the introductions to functional structure, principle, instructions, assemble language programming, interface and application of MCS-51single chip
DecisionTree
- 数据挖掘决策树算法,使用决策树实现分类问题-Data mining decision tree algorithm, using a decision tree to classify problems