Description: 一个马尔科夫分类算法，其中使用了马尔科夫估计方法，分类的精度高。-a classification algorithm, which used Markov estimation, classification of high accuracy. Platform: |
Size: 918079 |
Author:张云 |
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Description: 一个马尔科夫分类算法，其中使用了马尔科夫估计方法，分类的精度高。-a classification algorithm, which used Markov estimation, classification of high accuracy. Platform: |
Size: 917504 |
Author:张云 |
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Description: 隐马尔可夫模型源代码，可用于图像处理，分类，压缩，去噪等等。-Hidden Markov Model source code, can be used for image processing, classification, compression, denoising, etc.. Platform: |
Size: 696320 |
Author:王一笑 |
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Description: 有指导的马尔可夫随机场（MRF）的图像分割代码，是有指导的方式（即用鼠标框出分类样本区域）。采用OpenCV编写。-Has guided Markov Random Field (MRF) image segmentation code, is guiding the way (that is, a classification of the box with the mouse sample region). Prepared using OpenCV. Platform: |
Size: 5540864 |
Author:sdfadf |
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Description: HMM的c实现，对理解HMM很有用，尤其是动态手势识别中，手运动的建模基本都基于H-HMM of c realization of HMM is useful for understanding, especially in the dynamic gesture recognition, hand movements are based on modeling the basic H Platform: |
Size: 8192 |
Author:wdx |
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Description: 提出了一种基于函数联接的感知器神经网络的纹理分类方法.它采用高斯2马尔柯夫随机场模型(GM RF)对纹理进行描述,模型参数即为纹理特征,参数估计采用最小平方误差方法获得.将估计参数作为表达纹理的特征向量,用感知器网络对特征进行分类,并且采用函数联接的方式解决线性不可分问题.对纹理图象进行的实验表明,采用这种方法能够提高学习速度,简化计算过程,并取得较好的纹理分类效果.
-Based on the function connected perceptron neural network texture classification method. It uses 2 Gaussian Markov Random Field Model (GM RF) to describe the texture, the model parameters is the texture feature, parameter estimation using least squares error obtained. the estimated parameters as the expression of texture feature vector, using the characteristics of sensor networks for classification, and the use of function to resolve connection problems can not be separated from linear. of texture images of the experiments show that this approach can enhance the learning speed, to simplify the calculation process and obtain a better effect of texture classification. Platform: |
Size: 285696 |
Author:singro jiang |
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Description: CRF1.2，条件随机场软件包，很好用很流行的一个文本分类软件，可以用于自然 语言的处理，标签，分类，词性发现，用户只需要着重构造特征函数既可以，实验结果和应用表明crf要优于隐马尔科夫模型。实现环境为java语言。-CRF1.2, conditions package with the airport, very good very popular with a text classification software, can be used in natural language processing, labeling, sorting, part of speech found that users only need to focus on structural characteristic function can, experimental results and applications show that the CRF is superior to Hidden Markov Model. Environment for the realization of java language. Platform: |
Size: 2252800 |
Author:陈先开 |
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Description: In this paper pseudo 3-D Hidden Markov Models
(P3DHMMs) are applied to the task of dynamic facial expression
recognition. P3DHMMs are an extension of the
pseudo 2-D case, which has been successfully used for the
classification of images and the recognition of faces Platform: |
Size: 934912 |
Author:sagier |
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Description: SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X --> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
-SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X--> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
Platform: |
Size: 109568 |
Author:jon |
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Description: SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X --> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
-SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X--> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
Platform: |
Size: 117760 |
Author:jon |
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Description: Hiden Markov Model的C语言实现，目前比较好的一个实现。用于机器学习，模式识别，分类算法-Hiden Markov Model of the C language, an implementation of the present better. For machine learning, pattern recognition, classification algorithm Platform: |
Size: 273408 |
Author:Liang Ge |
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Description: 一些关于分层隐马尔可夫的几篇文章，是关于模式识别与分类的，希望对大家有所帮助-Hierarchical Hidden Markov about several articles on pattern recognition and classification, we want to help Platform: |
Size: 6176768 |
Author:zhaotao |
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Description: 《Software for Flexible Bayesian Modeling and Markov Chain Sampling》是机器学习领域专家Neal编写的用于Bayesian和马尔可夫链Linux下的C语言工具包。很有名，也很权威。
-This software supports Bayesian regression and classification models based on neural networks and Gaussian processes, and Bayesian density estimation and clustering using mixture models and Dirichlet diffusion trees. It also supports a variety of Markov chain sampling methods, which may be applied to distributions specified by simple formulas, including simple Bayesian models defined by formulas for the prior and likelihood. Platform: |
Size: 974848 |
Author:王磊 |
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Description: a novel algorithm to segment
an audio piece into its structural components.
The boundaries of the homogeneous regions are decided
based on various time and frequency domain
features. The algorithm has been designed in 2 stages.
In the first stage, a vocal/non-vocal/silence classification
is done using multinomial softmax regression. The
second stage uses a hidden Markov model to ‘smooth’
the previous output as well as enforce the time dependent
structuring. Platform: |
Size: 156672 |
Author:kvga |
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Description: In this paper we present the necessary theory to
detect fraud in credit card transaction processing using a
Hidden Markov Model (HMM). An HMM is initially trained
with the normal behavior of a cardholder. If an incoming
credit card transaction is not accepted by the trained HMM
with sufficiently high probability, it is considered to be fraudulent. Platform: |
Size: 162816 |
Author:phdscolar
|
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