搜索资源列表
CS4VM
- cs4vm算法，是实现半监督学习的较好的方法，能够对多种数据集进行测试，代码中包含例子，下载即可以使用-cs4vm algorithms, semi-supervised learning is to achieve a better way to test a variety of data sets, the code contains examples that can be used to download
harmonic_function
- 大牛所利用的半监督学习算法进行分类使用的调和函数的matlab实现-Daniel, the use of semi-supervised learning algorithm to classify the use of harmonic functions matlab implementation
meanS3VM
- means3vm算法，matlab 是实现半监督学习的较好的方法，能够对多种数据集进行测试，代码中包含例子，下载即可以使用-means3vm algorithm, matlab is better to achieve semi-supervised learning methods can be tested on a variety of data sets, the code contains examples that can be used to download
ssSVMToolbox-Bin.win32.win32.x86
- SSSvm， 半监督学习算法，文档在sourceforge上下载-SSSvm, semi-supervised learning algorithm, the document in the sourceforge download
learning_code
- 无限混合模型的非监督学习算法的例程和MATLAB代码-It s a set of MATLAB m-files implementing the mixture fitting algorithm.It consists of a main MATLAB function and three auxiliary functions.
patternRecognition
- 这系列课件系统地讲述了模式识别的基本理论和基本方法。内容涵盖了贝叶斯决策、概率密度函数的估计、线性判别函数、邻近法则、特征的选择和提取、非监督学习、神经网络、模糊模式识别等。-This series of courseware on a pattern recognition system to the basic theory and basic methods. Covers the Bayesian decision-making, the estimated probability de
PCA
- 主成份分析，一个最经典的无监督学习算法，也是最常用的线性降维方法-PCA
81404566ssl_survey
- 基于半监督学习的入侵检测技术研究 聚类程序- Intrusion Detection Algorithm Based on semi-supervised learning
work_for_pattern_recognition
- 通过设计线性分类器；最小风险贝叶斯分类器；监督学习法分层聚类分析；K－L变换提取有效特征，设计支持向量机对给定样本进行有效分类并分析结果。-By designing a linear classifier minimum risk Bayes classifier supervised learning method hierarchical cluster analysis K-L transform to extract efficient features, designed to
bayes
- 贝叶斯分类和后面的线性、非线性分类器属于有监督学习。 -Bayesian classification and the back of the linear, non-linear classifier belong to supervised learning.
SemiSupervisedLearning
- 第一本全面的半监督学习参考书，里面涵盖了半监督方面的各种算法，应用，以及理论证明-This is a comprehensive reference of semi-surpervised learning, including the algrithms, application, and the proof in theory.
spider1
- spider，很好用的模式识别工具箱，里面有各种分类工具，从有监督学习到无监督学习，从模型选择到参数选择。而且也将各个方法封装成类，使用方便。-spider, good use of pattern recognition toolbox, there are various classification tools, from supervised learning to unsupervised learning, choose Preferences from the model. But
active_learning
- 综合了主动学习和半监督学习的多项算法，很有价值的学习资料-Combination of active learning and a number of semi-supervised learning algorithm, learning valuable information
SemiL
- 利用基于图的分类方法， 半监督学习 ，分类软件。-SemiL is efficient software for solving large scale semi-supervised learning or transductive inference problems using graph based approaches.
机器学习梯度下降
- 机器学习监督学习算法，梯度下降、批梯度下降(Machine learning supervised learning algorithms, gradient descent, batch gradient descent.)
LDA_ FDA_with_tutorial
- LDA降维是常用的降维手段之一，是常用的有监督学习降维工具。这个文件对其产生W后的使用进行了简要说明，使用W进行最终的降维可以得到十分漂亮的分析结果（在数据分布符合假设分析的情况下。）(LDA dimension reduction is one of the commonly used dimensionality reduction methods. It is a commonly used supervised learning dimensionality reduction tool
半监督学习
- 半监督学习(Semi-Supervised Learning，SSL)是模式识别和机器学习领域研究的重点问题，是监督学习与无监督学习相结合的一种学习方法。半监督学习使用大量的未标记数据，以及同时使用标记数据，来进行模式识别工作。当使用半监督学习时，将会要求尽量少的人员来从事工作，同时，又能够带来比较高的准确性
主动半监督K_means聚类算法研究及应用_吕峰.caj
- 基于师生模型实现半监督学习，百万级数据级(Semi supervised learning based on teacher-student model, million data level)
机器学习实战书+源代码
- 机器学习横跨计算机科学、工程科学和统计学等多个学科，需要多学科的专业知识。在需要解释并操作数据的领域都或多或少可以运用到机器学习，通过这本书可以系统地学习基于python语言的机器学习的相关知识(Machine Learning in Action written by Peter Harringto. Machine learning covers many subjects, such as computer science, engineering science and statisti
kmeans聚类算法
- kmeans聚类分析，无监督学习实现Matlab代码(Kmeans clustering analysis, unsupervised learning implementation of MATLAB code)