搜索资源列表
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c++实现的KNN库:建立高维度的K-d tree,实现K邻域搜索，最小半径搜索-K-NN algorithm implementation.
It supports data structures and algorithms for both exact and approximate nearest neighbor searching in arbitrarily high dimensions.
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本算法是实现基于KNN的基因遗传算法，是对KNN算法的改进，具有更好的分类效果。-gaKnn[Genetic Algorithm Optimized K Nearest Neighbor Classification framework] is a frameowork for KNN optimization with a genetic algorithm.
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knn (k-nearest neighbor)用c++实现的近邻算法-knn (k-nearest neighbor) algorithm
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本次大作业利用K‐近邻（K‐Nearest Neighbor）算法，为给定的训练数据集构造了分类器，
并在测试数据集上进行分类预测，同时计算了Accuracy、Precision、Recall和F‐measure，利用
10‐fold的实验方法进行交叉验证。-The big job to use K-neighbor (K-Nearest Neighbor) algorithm, for a given set of training data classifier is constru
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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。-a machine learning algorithm
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K近邻算法，对一段数据进行分类，word 说明文档-K nearest neighbor algorithm
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传统基本K-最邻近分类算法源程序 云计算-Traditional basic K-nearest neighbor classification algorithm source code
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java语言实现的KNN算法代码。
KNN就是K最近邻(k-Nearest Neighbor，KNN)分类算法-java language code of the KNN algorithm. KNN is a K-nearest neighbor (k-Nearest Neighbor, KNN) classification algorithm
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一个用K近邻实现分类的算法，k最近邻算法是模式识别中的一种比较简单而经典的分类算法-Achieved with a K-nearest neighbor classification algorithms, k-nearest neighbor algorithm for pattern recognition is a relatively simple and classic classification algorithm
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关于K近邻算法的详细描述，包括算法原理及应用背景。-K-nearest neighbor algorithm on a detailed descr iption, including algorithm theory and application background.
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Delphi realization of k-nearest neighbor algorithm.
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In pattern recognition, the k-nearest neighbor algorithm (k-NN) is a method for classifying objects based on closest training examples in the feature space. k-NN is a type of instance-based learning, or lazy learning where the function is only approx
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提出了一种改进的散乱数据点k近邻搜索算法-An improved algorithm for searching points’k nearest neighbor is presented
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利用K近邻法实现数字识别算法。误差小，识别效率高，网络训练速度快。-K-nearest neighbor algorithm, digital identification algorithm. Error is small, high recognition efficiency and speed of network training.
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模式识别大作业K近邻算法（KNN）C++实现，内有iris和wine数据测试以及其他相关资料。-, Pattern Recognition large job K nearest neighbor algorithm (KNN) C++ achieved within the iris and wine data testing and other relevant information.
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用matlab实现K近邻算法，用于数据挖掘的分类-K-nearest neighbor algorithm for the classification of data mining using matlab
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采用快速K近邻与Kmeans聚类算法来计算前K个近邻，舍弃了一部分不可能成为待测样本的前K个近邻的训练样本，从而减少了计算量，提高了分类速度-Fast K-nearest neighbor Kmeans clustering algorithm to calculate the K nearest neighbors, abandoning the training samples of the part can not become the first K neighbors of the t
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借助于k-近邻算法，实现对酒品质的鉴定。并在算法中采用k值的调整以求结果更优。-By means of a k-nearest neighbor algorithm, identification of the quality of the wine. And k values used in the algorithm to adjust in order to better results.
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KNN邻近算法,程序运行结果显示所有样本以及其类别，待分类样本所属的类（{1,18,11,11,0.5513196}属于"2"类），以及它的5个最近邻的类别和与它之间的距离。内有详细说明文档。-k-Nearest Neighbor algorithm
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通过k近邻算法实现数字识别，主要包含0-9之间的所有数字。(Digital identification is realized by K nearest neighbor algorithm.)
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