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dbacl-1[1].3.1.tar
- dbacl是一个通用目的的digramic贝叶斯文本分类器。它可以学习你提供的文本，接着用学到的类别来比较新的输入。-dbacl is a general-purpose text digramic Bayesian classifier. It can learn to provide you with the text, then uses learned relatively new type of input.
netica_api
- 用于建立贝叶斯网络的netica工具的接口介绍，里面有具体实现的各种函数，方便通过其他例如c#,c等语言混合编程使用。-For the establishment of Bayesian network interface netica tools that there are concrete realization of the various functions to facilitate the adoption of other things such as c
BayesTree_0.2-0
- 为一个贝叶斯分类的学习算法实现,是基于linux系统下的c++实现-As a Bayesian classifier learning algorithm is based on linux systems c++ Achieve
gmmbayestb-v0.1.tar
- This package contains Matlab m-files for learning finite Gaussian mixtures from sample data and performing data classification with Mahalanobis distance or Bayesian classifiers. Each class in training set is learned individually with one of the three
MRICP2.0.tar
- This the MRICP driver for player/stage. This Driver is used as a localizer and Occupancy Grid Map Builder using simple Bayesian Probability Update. It uses Iterative closest Point method to allign laser scans and estimate the change of pose-This is t
Mrbayes_Gpu_Linux_Source_V1.0.tar
- 贝叶斯算法用CUDA实现后，Linux环境下编译，平均加速10倍左右！MR.Bayes 的GPU加速版-After the Bayesian algorithm achieved using CUDA, Linux environment, compiler, an average of 10 times! GPU-accelerated version MR.Bayes
bayes-sort
- 电子书，一篇论文，----用于分类规则挖掘的贝叶斯信念构造算法-For Classification Rule Mining Algorithm for Constructing Bayesian Belief
e16d17d2f6ba
- Face Recognition System with four methods: PCA, Bayesian, EBGM etc-Colorado University Face Recognition Source Code
withSmoothingBayes
- matlab下的贝叶斯分类器，经过平滑，大大提高了accuracy，可运行~-matlab Bayesian classifier, smoothed, and greatly improve the accuracy, you can run to
SRSoftware
- 超分辨重建，基于贝叶斯和总变分，牛人的文章对应的程序-Super-resolution reconstruction, based on Bayesian and total variation, cattle article corresponding program
lda-c
- LDA是一种文档主题生成模型，也称为一个三层贝叶斯概率模型，包含词、主题和文档三层结构。文档到主题服从Dirichlet分布，主题到词服从多项式分布。 LDA是一种非监督机器学习技术，可以用来识别大规模文档集（document collection）或语料库（corpus）中潜藏的主题信息。它采用了词袋（bag of words）的方法，这种方法将每一篇文档视为一个词频向量，从而将文本信息转化为了易于建模的数字信息。但是词袋方法没有考虑词与词之间的顺序，这简化了问题的复杂性，同时也为
iris_data_set
- 使用python语言 ， 实现对iris数据集的贝叶斯分类-Using the python language, the Bayesian classification of the iris dataset is achieved
442813
- Bayesian transform applied to image of function code, the matlab platform, has finished testing and debugging