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Neural Network Learning
- This book is about the use of artificial neural networks for supervised learning problems. Many such problems occur in practical applications of artificial neural networks. For example, a neural network might be used as
sime-kpca
- 基于半监督的核主元分析matlab代码，基于半监督核主元分析matlab代码-Based on the semi-supervised KPCA Matlab code, Based on the semi-supervised KPCA Matlab code
ssmcmcmatlab
- semi-supervised MCMC classification
LVQ
- LVQ(学习矢量量化)算法：它是Kohonen的有监督学习的扩展形式。融合了自组织和有导师监督的技术，学习方法是竞争的，但产生方式是有教师监督的，也就是说，竞争学习是在由训练输入指定的各类 中局部进行。-LVQ (learning vector quantization) algorithm: it is the Kohonen s supervised the expansion of the form of learning. Bl
111-30
- 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
quick-supervised-learning-throwaway-code-code(Matl
- 监督学习是机器学习中很重要的一种技术,该压缩包中是一个快速监督学习MatLab的实现程序-Supervised learning is very important in machine learning a technique, the compressed package is a fast supervised learning procedures realize the MatLab
Semisupervsedalignmenofmanifolds
- 一种半监督流形学习算法，包括相应的文章和代码。-A semi-supervised manifold learning algorithm, including the corresponding article and code.
UAIC
- 此算法利用一种有监督的人工免疫系统实现一个图像分类的分类器。-This algorithm used a supervised artificial immune system to achieve the classification of an image classifier.
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!
semi01
- 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
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
SDA
- Semi-Supervised Discriminant Analysis (Graph Embedding Way)
COREG
- Semi-supervised learning
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
sparse_coding
- .Sparse coding algorithm.We can also apply it onefficient sparse coding algorithm to a new machine learning fr a mework called "self-taught learning", where we are given a small amount of labeled data for a supervised le
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
2-Supervised Learning
- 2-Supervised Learning