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knn最近邻算法在给定新文本后，考虑在训练文本集中与该新文本距离最近（最相似）的 K 篇文本，根据这 K 篇文本所属的类别判定新文本所属的类别，具体的算法步骤如下：
一、:根据特征项集合重新描述训练文本向量
二、:在新文本到达后，根据特征词分词新文本，确定新文本的向量表示
三、:在训练文本集中选出与新文本最相似的 K 个文本-knn nearest neighbor algorithm in the given text, to consider in the train
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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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最近邻算法实现
k近邻
Z为训练集，每行一个样本，n*m
labZ为与Z对应的类别，列向量
Z_T为测试集，每行一个样本，p*m
labZ_T为输出结果,p*1-Nearest-neighbor algorithm
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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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KNN k s nearest neighbor algorithm-KNN k' s nearest neighbor algorithm
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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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最近邻法和K近邻法。作为分类器算法，k近邻法和最近邻法应用广泛-Nearest neighbor and K-nearest neighbor method. As a classifier algorithm, widely k nearest neighbor method nearest neighbor method and application
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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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kNN算法(k临近算法)的核心思想是如果一个样本在特征空间中的k个最相邻的样本中的大多数属于某一个类别，则该样本也属于这个类别，并具有这个类别上样本的特性。-The core idea of kNN algorithm is that if a sample in the feature space of k-nearest neighbor samples Most belong to a category, then the sample also fall into this catego
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型的类比学习方法是K-最近邻方法,它属于懒散学习法,相比决策树等急切学习法,具有训练时间短,但分类时间长的特点。K-最近邻算法可以用于分类和聚类中(The analogy learning method is K- nearest neighbor method. It belongs to the lazy learning method. Compared with the decision tree learning method, it has the characteristics o
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邻近算法，或者说K最近邻(kNN，k-NearestNeighbor)分类算法是数据挖掘分类技术中最简单的方法之一(The adjacent algorithm, or the K nearest neighbor (kNN, k-NearestNeighbor) classification algorithm is one of the simplest methods in the data mining classification technique)
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K nearest neighbor algorithm for indoor localization
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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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