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CS4VM is a package for efficient cost-sensitive semi-supervised learning. The package includes the MATLAB code of the algorithm CS4VM.
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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
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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
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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
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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
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sssvm相关的文档，也可以在sourceforge上下载-sssvm related documents, can also be downloaded at sourceforge
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wekaUT是 university texas austin 开发的基于weka的半指导学习(semi supervised learning)的分类器-university texas austin are wekaUT the development of guidance based on semi-weka study (semi supervised learning) classifier
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Semi-supervised learning
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kmeans均值聚类算法:一种改进的基于半监督聚类的入侵检测算法ASCID（Active-learning Semi-supervised Clustering Intrusion Detection），-kmeans clustering algorithm
Algorithm was simulated by KDD 99 datasets， which the experimental results demonstrate that ASCID algorithm can impro
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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
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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.
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对传统的支持向量机分类器的改进,利用了半监督学习的方法，可以极大的提高分类效率。-The traditional support vector machine classifiers is improved with a semi-supervised learning methods, can greatly improve classification efficiency.
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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
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利用支持向量机进行半监督学习的详细的文档，包括了部分伪代码，具有很大的参考价值-Using support vector machine semi-supervised learning of detailed documentation, including some pseudo-code, has great reference value
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Introduction to semi-supervised learning
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Semi-Supervised Learning Edited by
Olivier Chapelle,
Bernhard Scholkopf,
and Alexander Zien
2006 Massachusetts Institute of Technology
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义了一个欧氏距离和监督信息相混合的新的最近邻计算函数，从而将K一均值算法很好地应用于半
监督聚类问题。针对K一均值算法初始质心敏感的缺陷，用粒子群算法的搜索空间模拟聚类的欧氏空间，迭代搜
索找到较优的聚类质心，同时提出动态管理种群的策略以提高粒子群算法搜索效率。算法在UCI的多个数据集
上测试都得到了较好的聚类准确率。-Righteousness of a Euclidean distance and supervision of a mixture of new nearest n
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半监督学习非常好的一篇文章，机器学习重镇，南京大学写的，希望对大家有所帮助！-Semi-supervised learning is very good article, machine learning center, Nanjing University, write, we want to help!
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Semi-Supervised Distance Metric Learning for Collaborative Image Retrieval
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7 - Co-training A SEMI-SUPERVISED ENSEMBLE LEARNING ALGORITHM-6-7 - Co-training A SEMI-SUPERVISED ENSEMBLE LEARNING ALGORITHM-6
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