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source code for pattern classification k nearest neighbor source code
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KNN Classifier code and implementation with Visual Basic
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K最邻近分类器设计的MATLAB代码，有代码解释-K nearest neighbor classifier design in MATLAB code
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the method of feature extraction using pca and k nearest neighbor for recognition
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基于双低频小波变换和k近邻分类器的人脸识别算法源程序-Dual low frequency wavelet transform and k-nearest neighbor classifier based face recognition algorithm source
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本程序主要是实现knn算法，KNN(k Nearest Neighbors)算法又叫k最临近方法，在分类和模式识别方面都有重要的应用。-The program mainly knn algorithm ，KNN (k Nearest Neighbors) algorithm also known as k nearest neighbor method has important applications in classification and pattern recognition.
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对大量文件中相关内容的搜索，k近邻查询算法及一些改进-A large number of files in the search k nearest neighbor query algorithm and some improvements
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Basic implementation of k nearest neighbor algorithm. I have implemented it for a Machine Learning lecture homework.
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K nearest neighbor search for matlab
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k nearest neighbor algorithm for matlab
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是K最邻近结点算法（k-Nearest Neighbor algorithm）的缩写形式，是电子信息分类器算法的一种。KNN方法对包容型数据的特征变量筛选尤其有效。-k-Nearest Neighbor algorithm， It is a very useful matlab code.
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Implement the K nearest neighbor algorithm by your own instead of using available software.
2. Use K-fold cross validation to generate training and testing datasets. You should try different K values (3~8) to see how they affect your result.
3. T
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用matlab实现Part1. 实现一个k近邻分类器，Part 2.实现一个最小二乘分类器，Part 3.实现一个支持向量机分类器，Part 4.在不同数据集上使用交叉验证选择各个算法的参数-Part1. Achieve a k-nearest neighbor classifier, Part 2. Achieve a least-squares classifier, Part 3. Implement a support vector machine classifier, Part 4.
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KNN-是K最邻近结点算法（k-Nearest Neighbor algorithm）的缩写形式，是电子信息分类器算法的一种。KNN方法对包容型数据的特征变量筛选尤其有效。-In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method for classification and regression, that predicts objects "values"
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Iris 是一种鸢尾属植物。在数据记录中，每组数据包含Iris花的四种属性：萼片长度，萼片宽度，花瓣长度，和花瓣宽度，三种不同的花各有50组数据. 这样总共有150组数据或模式。这里用K近邻法进行分类。-Iris is a genus Iris. In the data recording, the data containing each of the four attributes Iris Flower: sepals length, sepal width, petal length,
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本程序实现了最近邻分类器的K近邻算法。实现方式是使用matlab-This program implements a nearest neighbor classifier K-nearest neighbor algorithm. Implementation using matlab
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matlab用于计算K近邻互信息量程序，多变量相关性(K nearest neighbor mutual information computing program)
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#k-近邻算法 实现 KNN 分类算法
# 对未知类别属性的数据集中的每个点依次执行以下操作：
# (1)计算已知类别数据集中的点与当前点之间的距离
# (2)按照距离递增次序排序
# (3)选取与当前点距离最小的K个点
# (4)确定前K个点所在类别的出现频率
# (5)返回前K个点出现频率最高的类别作为当前点的预测分类(#k-Nearest Neighbor , KNN)
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k-nn算法 K-NN算法 ( K Nearest Neighbor, K近邻算法 ), 是机器学习中的一个经典算法, 比较简单且容易理解. K-NN算法通过计算新数据与训练数据特征值之间的距离, 然后选取 K (K>=1) 个距离最近的邻居进行分类或者回归. 如果K = 1 , 那么新数据将被分配给其近邻的类.(k-nnK - NN algorithm (K on his Neighbor, K Nearest Neighbor algorithm), is a classical al
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调用于sklearn平台的K-Nearest Neighbor Classifier算法，有着较好的分类能力(The k-nearest Neighbor Classifier algorithm for sklearn platform has good classification ability.)
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