搜索资源列表
CKPCA-HOG-SVM
- 为了准确地对监控场景中的运动目标进行语义上的分类，提出了一种基于聚类的核主成分分析梯度方向直方图和二又决策树支持向量机的运动目标分类算法。-In order to accurately monitor the movement of scene targets semantic classification, the clustering based on kernel principal component analysis of gradient direction histograms,
mill
- 包含了很多分类算法，有SVM，knn，决策树等，还有文档说明-Contains a lot of classification algorithms, there is SVM, knn, decision tree and so on, have documented
SVMDecision
- VM分类器通常具有较高的分类精度。我这里不想过多的去说SVM是怎么回事，只是提供一种使用SVM进行判别的方法。决策树与SVM的结合，可以分多类。-VM classifier usually has a higher classification accuracy. I do not want too much here to say how the matter SVM, SVM is used to provide a method for identification. The combin
mushroom
- /* The sample demonstrates how to build a decision tree for classifying mushrooms. It uses the sample base agaricus-lepiota.data from UCI Repository, here is the link: Newman, D.J. & Hettich, S. & Blake, C.L. & Merz, C.J. (1998). UCI Repos
literature
- 几篇关于SVM研究的相关论文，主要是关于支持向量机决策树方面的-Several related papers on the SVM research, mainly on the aspects of support vector machine decision tree
HOG
- 为了准确地对监控场景中的运动目标进行语义上的分类， 提出了一种基于聚类的核主成分分析梯度方向直方图和二叉决策树支持向量机的运动目标分类算法．利用背景减法提取运动目标前景区域， 并识别出潜在候选运动目标．利 用提出的基于聚类的核主成分分析的梯度直方图描述子提取候选运动目标的特征， 以较低维数的数据有效地描述运动目标的有效特征． 将提取的运动目标特征输入二叉决策树支持向量机， 实现多类目标的准确分类． 通过在不同视频序列上的实验验证， 提出的算法对运动目标进行较好地分类， 而且在运算速度方面较传
VSVMDecisionM
- VM分类器通常具有较高的分类精度。我这里不想过多的去说SVM是怎么回事，，只是提供一种使用SVM进行判别的方法。决策树与SVM的结合，可以分多类。 -VM classifier usually has high classification accuracy. I do not want too much to say that SVM is how, just a SVM is used to discriminate. Combination of decision tree and S
SVM
- SVM算法的一个windows下实现，用决策树实现预测农产品质量，数据存放于SQLServer中，ADO方式存取。-SVM algorithm a windows with decision tree predictive quality of agricultural products, the data stored in SQLServer ADO accessed.
A-complete-fuzzy-discriminant
- Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference.
A-Component-based-Framework
- Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference.
a-direct-lda-algorithm
- Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference.
A-linear-discriminant
- Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference.
A-new-LDA-based-face
- Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference.
c4.5-decision-tree-matlab
- c4.5分类器 支持向量机算法 文本分类 样本支持 核函数算法-c4.5 classifier SVM text classification algorithm sample support kernel function
machine-learning
- python3实现各种机器学习算法，包括knn算法，决策树算法，SVM算法，朴素贝叶斯算法等-Python3 realize all kinds of machine learning algorithms, including KNN algorithm, the decision tree algorithm, the SVM algorithm, naive bayesian algorithm, etc
svm_dm
- 一个数据挖掘项目，使用到支持向量机，决策树，等方法-dm，svm，decision tree
Mechine_Learning
- 该功能包含决策树、随机森林、SVM机器学习算法，并在VS环境下实现并测试。-This function contains the decision tree, random forests, SVM machine learning algorithms, and implement and test in VS environment.
rough-set-codes
- 这是天津大学胡清华老师在粗糙集邻域领域做的最经典的源码，同学们可以在此基础上学习和修改，入口程序已经写好，需要其他方法可以自己添加，MAIN.m是入口程序，参数的意思在子函数里讲的很明白，调用了featureselect_FW_fast.m用来属性约简，几个clsf_dpd文件是使用不同的距离公式来计算属性重要度，选择得到属性结果，使用crossvalidate.m十折交叉算法来计算计算算法精度，该段代码调用了几个分类器，C4_5.m是决策树，KNN.m是最近邻分类器，NEC.m是类似于KNN的
machine_learning_inaction
- 机器学习十大算法实现，包括决策树、logisitic回归、SVM、数据降维等(Ten algorithms for machine learning, including decision tree, logisitic regression, SVM, data reduction and so on)
19107matlab自编svm
- 利用原算法adaboost弱学习器基于决策树桩的方法对样本数据进行多分类(Multi-classification of sample data based on decision tree stump using AdaBoost weak learner)