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kNN
- KNN，k近邻算法，内附测试数据集，机器学习实战源码-KNN, k nearest neighbor algorithm, enclosing the test data set, machine learning practical source
knn
- K近邻分类算法实现 in Python -KNN Classfier in Python
K-Nearest-Neighbor
- 数据挖掘中经典的KNN（K-最近邻）算法，导入即可运行-Data Mining the classical KNN (K- nearest neighbor) algorithm, you can import operation
KNN
- K近邻算法的python代码，针对婚恋网站调查数据-the python code especially for k-nearest algorithm on the condition of wedding data
KNN-implement-by-python
- 该程序是用python编写一个K近邻算法，通过该例子可以掌握K近邻算法，是学习数据挖掘的一个高效的算法。-The program is written in python a K-nearest neighbor algorithm, this example can grasp the K-nearest neighbor algorithm, a learning data mining and efficient algorithms.
kNN
- k近邻算法，可以简单准确的对数据，按照给定点与设定点的欧氏距离大小，进行分类-K nearest neighbor algorithm, can be simple and accurate data, in accordance with the set point to the point and the Euclidean distance of the set point size, classification
最近邻分类代码
- 在linux 下C语言实现最近邻聚类算法，工程已经使用(near K neighbor cluster)
knn
- 模式识别中的k近邻算法，经过测试，运行结果很好。 最小距离分类器 : 它将各类训练样本划分成若干子类，并在 每个子类中确定代表点 。测试样本的类别则以其与这些代表点距离最近作决策。该方法的缺点是所选择的代表点并不一定能很好地代表各类，其后果将使错误率增加。(The k nearest neighbor algorithm in pattern recognition has been tested and the result is very good. Minimum distance c
PCA+mnist
- 基于python，利用主成分分析（PCA）和K近邻算法（KNN）在MNIST手写数据集上进行了分类。 经过PCA降维，最终的KNN在100维的特征空间实现了超过97%的分类精度。(Based on python, it uses principal component analysis (PCA) and K nearest neighbor algorithm (KNN) to classify on the MNIST handwritten data set. After PCA dime