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模式识别一份很好的作业,包括线性分类器；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,支持向量机-a very good operation, including linear classification; Minimum risk Bayesian classifier; Supervised learning method Hierarchical clustering analysis; K-L transform effective features, supp
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Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more.
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基于自组织特征映射网络的聚类分析，是在神经网络基础上发展起来的一种新的非监督聚类方法，分析了基于自
组织特征映射网络聚类的学习过程，分析了权系数自组织过程中邻域函数和学习步长的一般取值问题，给出了基于自组织
特征映射网络聚类实现的具体算法，并通过实际示例测试，证实了算法的正确性。
-Based on self-organizing feature map network cluster analysis, neural network is developed on the basi
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Meanshift的非监督聚类方法,主要用于图像处理和模式识别。-Meanshift non-supervised clustering method, mainly used in image processing and pattern recognition.
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ISODATA算法是一种基于统计模式识别的，非常经典的非监督学习动态聚类算法，有较强的实用性。ISODATA算法不仅可以通过调整样本所属类别完成样本的聚类分析，而且可以自动地进行类别的“合并”和“分裂”，从而得到类数比较合理的聚类结果。-ISODATA algorithm is based on statistical pattern recognition, and very classic dynamic clustering of non-supervised learning algor
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AP是在数据点的相似度矩阵的基础上进行聚类.对于规模很大的数据集,AP算法是一种快速、有效的聚类方法,这是其他传统的聚类算法所不能及的,-A semi-supervised clustering method based on affinity propagation (AP) algorithm is proposed in this paper. AP takes as input measures of similarity between pairs of data points. AP
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用Ｋ均值和遗传算法实现了半监督聚类算法，这是个一个已经发表的论文的源程序-Using K-means and genetic algorithm to achieve a semi-supervised clustering algorithm, this is a paper published source
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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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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
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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
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基于支持向量机与无监督聚类相结合的中文网页分类器，好文章-un supervised clustering
algo rithm
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一本将基于近邻传播算法的半监督聚类的算方法书.对于聚类研究的很有帮助-Abstract: A semi-supervised clustering method based on affinity propagation (AP) algorithm is proposed in this
paper. AP takes as input measures of similarity between pairs of data points. AP is an efficient a
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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
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使用有监督的近邻传播聚类算法进行特征波段选取-Neighbors using a supervised clustering algorithm for propagation characteristics of selected bands
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实现半监督聚类，针对weka框架进行扩展。-It realize semi-supervised clustering method. And it is extension of weka.
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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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利用谱聚类方法在特
征向量空间中对原始样本数据进行重新表述使得在新表述中同一聚类中的样本能够更好地积聚在一起构建聚类核函数 并进而构造聚类核半监督支持向量机 使样本更好地满足半监督学习必须遵循的聚类假设 -Restated in the new formulation in the same cluster sample be better able to accumulate together to build the clustering of nuclear function and
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基于PCA有监督kohonen网络的网络入侵聚类。里面包含有原代码和说明文件。-Based on PCA supervised kohonen network clustering network intrusion
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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
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This file belongs to semi supervised clustering
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