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sparse_coding
- .Sparse coding algorithm.We can also apply it onefficient sparse coding algorithm to a new machine learning framework called "self-taught learning", where we are given a small amount of labeled data for a supervised learning task, and lots of additio
SDA
- 半监督分类分析。注释有对应的参考文献和使用说明！-Semi-supervised classification analysis. Notes there is the corresponding references and the use of note!
wekaUT.tar
- 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
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
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.
KNN1
- knn algorithm to classify data in an supervised way-knn algorithm to classify data in an supervised way..
knnsearch_data
- knn search data algorithm to classify data in an supervised way
ICA-app
- ica application algorithm to classify data in an supervised way
enhancing_semi_supervised
- enhancing semi-supervised clustering:a feature projection prespective算法实现-the implementation of the alogrithm described in the paper--- enhancing semi-supervised clustering:a feature projection prespective
LSFS
- 有监督的特征选择和优化程序MATLAB代码，基于最小二乘算法。内有测试数据，和详细程序说明-Least-Squares Feature Selection (LSFS) is a feature selection method for supervised regression and classification. LSFS orders input features according to their dependence on output values. Dependency bet
p1
- hallenge to the use of supervised neural networks in data mining applications is to get explicit knowledge from these models. For this purpose, a clustering genetic algorithm for rule extraction from artiÞ cial neural networks is developed. T
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
SSIsomap1
- semi supervised Isomap,matlab codes.
ap_semisupervised
- Semi-supervised Affinity Propagation clustering.基于AP聚类的半监督学习算法。-The programs of semi-supervised AP are suitable for the person who has interests in studying or improving AP algorithm, and then the semi-supervised AP may be an example for reference
Semi-Supervised-Kernel-Based-Fuzzy
- 研究半监督学习的模糊核聚类方法用于变速箱早期故障诊断的方法。故障特征不明显、样本差异小是机械故障早期检测的 难点， 基于半监督学习的核聚类方法利用少量已知模式的样本， 结合大量未知模式的样本进行半监督学习， 得到较好的识别效果。-In this paper, motion control method of semi-closed CNC method is presented for gear-box fault early detection. The difficulty mach
Semi-supervised-learning
- 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
Semi-supervised-learning-NJU
- 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!
Semi-Supervised-Distance-Metric
- Semi-Supervised Distance Metric Learning for Collaborative Image Retrieval
semi-supervised-algorithm-matlab
- 半监督分类算法，其中有一些例子可供大家使用-semi-supervised algorithm，there are examples you can try。
semi-supervised-cluster-algorithm
- 半监督聚类是利用少量的标记数据提高聚类算法的性能，文中综述了半监督聚类算法的若干进展-Semi supervised clustering is a method to improve the performance of clustering algorithm by using a small amount of labeled data,Some advances about semi supervised clustering algorithms are reviewed in thi