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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
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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 tex
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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
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《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 Ba
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DHMM,离线隐马尔科夫模型用于模式分类的好例子,特征采用Kmeans进行离散化。-DHMM, off-line Hidden Markov Model good example for pattern classification, feature discretization using Kmeans.
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Patter Classification Duda 2nd 书中Example的代码 Hidden Markov Models前向算法,后向算法以及译码算法-HMM Forward Algorithm
HMM Backward Algorithm
HMM Decoding Algorithm
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特征训练识别的嵌入式隐马尔可夫模型代码,可用于人脸识别的分类-Training recognition feature embedded hidden Markov model code, can be used for face recognition classification
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这是一个隐马尔可夫模型前向算法,各位亲可以下载使用,一般用于计算分类,预测,-This is a hidden Markov model before the algorithm, you can download pro, generally used to calculate the classification, prediction, etc.
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Image classification by a Two Dimensional Hidden Markov Model
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分类判别
马氏距离 贝叶斯 广义平方距离 Fisher判别-Classification discriminant
Bayesian markov distance of generalized square distance Fisher discriminant
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使用Contourlet变换和SVM进行书画艺术的识别,通过EM算法进行HMT参数的训练-Code used for the article Authentication of paintings using hidden Markov modelling of contourlet transforms , where we develop a method for classification of paintings digital reproductions.
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可以分别设置度量距离的KNN分类器,有欧式和马氏距离。对模式识别十分重要的作用,有着较好的分类效果,可以帮助新手更好的理解KNN原理,对人脸识别有着很好的演示作用。-Distance can be set respectively KNN classifier, style and markov distance. For pattern recognition is an important role, has a good classification effect, can help be
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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
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K最邻近密度估计技术是一种分类方法,不是聚类方法。
不是最优方法,实践中比较流行。
通俗但不一定易懂的规则是:
1.计算待分类数据和不同类中每一个数据的距离(欧氏或马氏)。
2.选出最小的前K数据个距离,这里用到选择排序法。
3.对比这前K个距离,找出K个数据中包含最多的是那个类的数据,即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering metho
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K最邻近密度估计技术是一种分类方法,不是聚类方法。
不是最优方法,实践中比较流行。
通俗但不一定易懂的规则是:
1.计算待分类数据和不同类中每一个数据的距离(欧氏或马氏)。
2.选出最小的前K数据个距离,这里用到选择排序法。
3.对比这前K个距离,找出K个数据中包含最多的是那个类的数据,即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering metho
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使用模拟退火算法进行SVM超参数优化,NASA 开源软件。(Mariana is an algorithm that efficiently optimizes the hyperparameters for Support Vector Machines for regression and classification. It currently uses Simulated Annealing for optimization but can be extended to use a va
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