Description: 模式识别相关技术，EM算法简介，EM算法是关于半监督学习的一种技术-Pattern recognition technology, EM algorithm About, EM algorithm is on a semi-supervised learning techniques Platform: |
Size: 123904 |
Author:lulu |
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Description: 近三年来半监督学习的国外顶级期刊论文，办监督的最新研究成果-Over the past three years semi-supervised learning of foreign top-level journal articles, to do oversight of the latest research results Platform: |
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Author:jz |
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Description: 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 Platform: |
Size: 12618752 |
Author:尹朝明 |
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Description: 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. Platform: |
Size: 5501952 |
Author:高阳 |
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Description: 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. Platform: |
Size: 11264 |
Author:苏航 |
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Description: 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 Platform: |
Size: 2048 |
Author:苏航 |
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Description: 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 Platform: |
Size: 478208 |
Author:苏航 |
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Description: Semi-Supervised Learning Edited by
Olivier Chapelle,
Bernhard Scholkopf,
and Alexander Zien
2006 Massachusetts Institute of Technology Platform: |
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Author:Azarm |
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Description: 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 neighbor calculation functions, thus the K-means algorithm applied to the semi-supervised clustering problem. K-means algorithm the initial center of mass-sensitive defect clustering in the search space of the particle swarm algorithm simulation in Euclidean space, an iterative search to find the optimum cluster centroid, and strategies to improve particle swarm optimization to dynamic management of stocks search efficiency. Algorithm on multiple datasets in the UCI tests are a good clustering accuracy. Platform: |
Size: 423936 |
Author:xz |
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Description: A PhD thesis on Semi-supervised learning with Graphs by Xiaojin Zhu. Focuses on creating graphs, based on a mixture of labeled and unlabeled data (as per the semi-supervised learning paradigm) and using processes on these graphs to propagate in rigorous way the labels from the labeled data to the unlabeled.
Applications in various areas in the Machine learning, such as text processing, image processing, pattern recognition, and others. Platform: |
Size: 2542592 |
Author:stefan.petrov.beb |
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Description: 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! Platform: |
Size: 1591296 |
Author:zhuwentao |
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Search - semi Supervised learning