搜索资源列表
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用matlab写的最近邻和K近邻法分类器，简单易懂，适合初学者,Written with matlab and K-NN nearest neighbor classifier, easy to understand for beginners
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常用的分类方法，包括最近邻（NN），k均值（kmeans），k近邻，Fisher线性判别。-Commonly used classification methods, including nearest-neighbor (NN), k the mean (kmeans), k neighbors, Fisher linear discriminant.
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k Nearest Neighbor matlab code
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一个matlab环境下的k近邻分类器,代码中有详细的注释说明,使用方便.-K-Nearest-Neighbor-Classifier MatLab Code
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knn-K近邻法实现两分类的函数代码，输入为两类的样本特征，和待测试的样本向量，输出为分类结果。-knn-K nearest neighbor method to achieve the two categories of function code, enter the characteristics of two types of samples, and samples to be tested vector, the output for the classification.
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K近邻算法（KNN）的matlab源代码，程序清晰易读-K nearest neighbor (KNN) of matlab source code, procedures legible
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K近邻算法在Matlab中的实现，相当完整，对研究KNN算法有一定帮助-K nearest neighbor in the Matlab, implementation, rather complete, the study of KNN algorithm has certainly helped
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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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K-PNN Algorithm
a type of k nearest neighbor algorithm
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fuzzy k-nearest-neighbor algotithm-fuzzy k-nearest-neighbor algotithm
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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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寻找测试样本的最近邻，可以有效的用于用于模式识别，信号处理-This is a small but efficient tool to perform K-nearest neighbor search, which has wide Science and Engineering applications, such as pattern recognition, data mining and signal processing.
The code was initially
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MATLAB 小程序，可以实现模式识别中的K近邻算法，已经运行成功，附运行程序结果-MATLAB small programs can be achieved in the K-nearest neighbor pattern recognition, has been running successfully run the program attached to the results of
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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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灰度共生矩阵提取特征值，最近邻算法，进行纹理图像分类。creat_apprentissage用来训练样本，cooccurence是灰度共生矩阵提取特征值，knn是进行k最近邻算法，classif是纹理图像分类-coocurence matrix，using K nearest neighbor to classify textures images.
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K邻域模式识别方法 KNN算法不仅可以用于分类，还可以用于回归。通过找出一个样本的k个最近邻居，将这些邻居的属性的平均值赋给该样本，就可以得到该样本的属性。更有用的方法是将不同距离的邻居对该样本产生的影响给予不同的权值(weight)，如权值与距离成正比。-k-Nearest Neighbor algorithm
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这个程序是用来寻找每个图像的K近邻的，然后得到了一个权值矩阵-This program is used to find K-nearest neighbor of each image, and then get a weight matrix
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code of implementing the K-Nearest Neighbor method
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模式识别实验 k最近邻估计MATLAB程序-Pattern recognition experiments k nearest neighbor estimation MATLAB program
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