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ICA_demo_text
- ICA is used to classify text in extension to the latent semantic indexing framework. ICA show to align the context grouping structure well in a human sense [1], thus can be used for unsupervised classification. The demonstration shows this on medical
apcluster
- 无监督聚类算法,能够自动聚类,不必预先给出类数,聚类精度好于常用的聚类算法.-Unsupervised clustering algorithm, can automatically cluster, do not have to give in advance the number of categories, clustering accuracy of better than commonly used clustering algorithm.
EM-algorithm
- EM算法，是一种无监督的聚类算法，可以实现对数据的处理，对不同数据进行聚类，生成类内相似度最大-EM algorithm is an unsupervised clustering algorithm, the data processing can be achieved on different data clustering, to generate the maximum within-class similarity
shang
- 一种无监督的数据离散化方法，程序简单，运行时间短，效果比较显著-An unsupervised data discretization methods, procedures easy, run a short time, compared the effect of significantly
som(Jal.You)
- SOM神经网络（自组织特征映射神经网络）是一种无导师神经网路。网络的拓扑结构是由一个输入层与一个输出层构成。输入层的节点数即为输入样本的维数，其中每一节点代表输入样本中的一个分量。输出层节点排列结构是二维阵列。输入层X中的每个节点均与输出层Y每个神经元节点通过一权值(权矢量为W)相连接，这样每个输出层节点均对应于一个连接权矢量。 自组织特征映射的基本原理是，当某类模式输入时，其输出层某一节点得到最大刺激而获胜，获胜节点周围的一些节点因侧向作用也受到较大刺激。这时网络进行一次学习操作，获胜节点
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
EM-GMM
- Em algo for GMM, data mining unsupervised learning-Em algo for GMM, data mining unsupervised learning
k_means
- k均值的 咱们做非监督分类都用过 不想理解他的原理吗 很重要-k mean we do not want unsupervised classification are used to understand his theory is very important to you
SOMToolBox
- This is unsupervised learning SOM Toolbox for matlab
kmeans2
- k-means image segmentation algorithm
DBSCAN
- BIRCH (balanced iterative reducing and clustering using hierarchies) is an unsupervised data mining algorithm used to perform hierarchical clustering over particularly large data-sets. An advantage of Birch is its ability to incrementally and dynamic
BAMIC
- BAMIC是一种multi-instance聚类的算法。-BAMIC is a package for multi-instance clustering. This package includes the MATLAB implementation of BAMIC, which is designed to deal with unsupervised multi-label learning problems. It is particularly useful when real-wo
Neurons-PID-control
- 采用四种埪制律进行单神经元PID控制，即无监督的Hebb学习规则；有监督的Delta学习规则；有监督的Hebb学习规则；改进的Hebb学习规则。-Kong legal system of four single-neuron PID control, the Hebb learning rule is unsupervised a supervised learning rule Delta a supervised Hebb learning rule modified Hebb lea
GMM
- 无监督混合高斯模型（GMM）的EM估计，含两篇IEEE论文的源码-This is a set of MATLAB m-files implementing the mixture fitting algorithm described in the paper M. Figueiredo and A.K.Jain, "Unsupervised learning of finite mixture models", IEEE Transaction on Pattern Analys
Unsupervised-optimal-FCM
- Fuzz c-mean Clusterin technique
rwrelease.tar
- Andrew N.G. 教授于2011年机器学习国际会议(ICML)发表了文章Code for On Random Weights and Unsupervised Feature Learning， 文件是paper的实现代码，非常具有参考价值-Professor Andrew NG 2011 machine learning Article Code for On the Random Weights and Unsupervised Feature Learning Internation
kmeans_demo
- 这是安德鲁教授在AISTATS上发表的文章An Analysis of Single-Layer Networks in Unsupervised Feature Learning对应的实现code,很有学习价值-Andrew Professor post in AISTATS An Analysis of Single-Layer Networks in Unsupervised Feature Learning corresponding implementation code, is le
Process
- Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reductio
Unsupervised-Statistical-Models-for-General-Objec
- Unsupervised Statistical Models for General Object Recognition
Unsupervised-cluster-analysis
- 关于非监督聚类分析的一些matlab编程的列子，初学者可以-Unsupervised cluster analysis on some matlab programming Liezi, beginners can take a look at