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这是用来进行模式识别的参考程序，程序对输出结果给出了比较形象化的结果-This is used for the reference pattern recognition procedures, procedures for a given output compared to visualize the results
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优化算法loqo的算法源代码。Purpose: solves quadratic programming problem for pattern recognition for support vectors
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k-nn算法实现分类，模式识别作业，分三类，75个训练集，25个测试集，输出对测试集分类的结果,k-nn classification algorithm, pattern recognition operations are classified into three types, 75 training sets, 25 test set, the output of the test set classification results
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support vector machines (C), can be used for pattern classification, pattern recognition.
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应用于模式分类中，用模式匹配方法对数据进行分类来获得对手写汉字识别的功能-Applied to pattern classification, the use of pattern-matching methods to classify the data to obtain the function of Handwritten Chinese Character Recognition
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运用模式识别中k临近法对数据进行分类，只要随意更改KEY的值为某一身高或体重，则可判别分类为A女或B男。-K using the approach of pattern recognition method to classify the data, as long as the random changes in the value of KEY for a height or weight, can be classified as A female judge or B M.
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the classic pattern recognition algorithms, dynamic clustering algorithm k mean using Matlab programming, as well as classification of the class analysis
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模式识别与智能计算的matlab实现，全书数据文件，许国根编写的，直接可以导入matlab中使用-Pattern Recognition and Intelligent Computing matlab realize, the book data files, Xu root preparation, can be imported directly using matlab
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机器学习和模式识别工具包spider。内容很丰富。包含svm 决策树（C45,J48）、svm、knn、adaboost、bagging、hmm（隐马尔科夫模型）、随机树（random forest）等-Machine learning and pattern recognition toolkit spider. Very rich in contents. Tree contains svm (C45, J48), svm, knn, adaboost, bagging, hmm (hidd
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数据聚类 (英语 : Cluster analysis) 是对于静态数据分析的一门技术，在许多领域受到广泛应用，包括机器学习，数据挖掘，模式识别，图像分析以及生物信息。聚类是把相似的对象通过静态分类的方法分成不同的组别或者更多的子集（subset），这样让在同一个子集中的成员对象都有相似的一些属性，常见的包括在坐标系中更加短的空间距离等。-Data Clustering (English: Cluster analysis) for a static data analysis techniqu
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and parallel implementation, and its portfolio optimization, machine learning, image processing, process control, evolutionary neural networks, Fuzzy Pattern Recognition and Artificial Life
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线性分类器可以实现线性可分的类别之间的分类决策，其形式简单，分类决策快速。但在许多模式识别的实际问题中，两个类的样本之间并没有明确的分类决策边界，线性分类器（包括广义线性分类器）无法完成分类任务，此时需要采用其它有效的分类方法。贝叶斯分类器就是另一种非常常见和实用的统计模式识别方法。-Linear classifier can be realized linearly separable classification decision between classes in the form of
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模式识别中贝页斯分类器的MATLAB实现,且用不同颜色标记了分类点和错分点-Mr Page in pattern recognition classifier of MATLAB, and use different color tag by classification and fault point
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模式识别中贝页斯分类器的MATLAB实现,且用不同颜色标记了分类点和错分点-Mr Page in pattern recognition classifier of MATLAB, and use different color tag by classification and fault point
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For pattern recognition problem of k-means also calls the c-means matlab are given,
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模式识别中,对于服从多元正态分布的样本的一个分类器的实现,-Pattern recognition, for the sample of multivariate normal distribution on the implementation of a classifier,
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