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natlab源程序，k近邻的程序，希望对大家有用-natlab source, k neighbor procedure, in the hope that useful
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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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Image thresholding has played an important role in image segmentation. In this paper, we present a novel spatially weighted fuzzy c-means (SWFCM) clustering algorithm for image thresholding. The algorithm is formulated by incorporating the spatial ne
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k NN algorithm nearest neighbor search
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k近邻问题，我自己做的，效果有保证，还有测数据-k neighbor problem, I do, the effect is guaranteed, as well as measured data
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In this paper, we show how support vector machine (SVM) can be
employed as a powerful tool for $k$-nearest neighbor (kNN)
classifier. A novel multi-class dimensionality reduction approach,
Discriminant Analysis via Support Vectors (SVDA), is in
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k近邻算法(knn, k nearest neighbor)-k nearest neighbor (knn, k nearest neighbor)
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使用K近邻方法对给定的一个样本进行分类。-K nearest neighbor method using a sample of a given classification.
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模式识别中的k近邻算法，用matlab编写，希望对大家有所帮助-K-nearest neighbor algorithm for pattern recognition with matlab write, we want to help
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K近邻方法实现0到9数字的模式识别问题。可扩展性很强，方面实现训练和识别。-K nearest neighbor method to achieve 0 to 9 digit pattern recognition problem. Highly scalable, achieving training and recognition.
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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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K近邻法对Iris数据分类，输入分类结果和准确率。-K-nearest neighbor method for Iris data classification, enter the classification results and accuracy.
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Delphi realization of k-nearest neighbor algorithm.
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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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K邻近快速算法，包含有独立的样本分解算法，树搜索算法，稍作改动便可以满足各种要求。-K adjacent fast algorithm contains a separate sample decomposition algorithm, the tree search algorithm, some minor changes will meet a variety of requirements.
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模式识别中用于完成数据的分类而用到的一种方法-k近邻。是将已有数据划分到3个类中，本方法中解决数据Iris数据的划分问题。将150个4维数据划分到3类。K近邻法是求最近的K个元素从而将其划分到已有类中。-Pattern recognition for the completion of the classification of the data used in a way-k neighbors. The existing data are divided into three classes
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给出了一种基于距离的模糊隶属度定义形式，通过这种定义来改进K-近邻算法，得到一种自己定义的模糊K-近邻算法。同时本文中给出编程流程，编程思想以及实验结果。-A distance-based definition of fuzzy membership form, by this definition to improve K-nearest neighbor algorithm to obtain a defined fuzzy K-nearest neighbor algorithm. The
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k近邻法分类iris数据。iris数据共分三类，每一类50个数据，这里把每一类前20个作为训练样本，后30个作为测试样本-k-nearest-neighbor classification iris data. iris data is divided into three categories, each category of data from 50, as the training samples in each category of the top 20 after 30 as th
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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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自适应空间球的k邻域快速搜索算法，利用空间微分块与动态球策略的k近邻搜索算法研究-Origianl-Adaptive spatial neighborhood k ball fast search algorithm, differential block the use of space and dynamic ball strategy k nearest neighbor search algorithm-Origianl
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