搜索资源列表
KNN-matlab
- k近邻的两种改进算法，采用matlab实现，使得算法效率有了较大提高。-two methods for knn，both of them are run in matlat.
KNN
- 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.
kNN
- 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
srknn
- 自己用matlab编写实现的一个k近邻算法，并有训练和测试数据，能运行。附有注释，简单清晰。-a k-nearest neighbour algorithm developped using matlab.
Classification
- VC++中实现K近邻分类方法，实验数据是著名的iris数据库，此方法是数据挖掘，机器学习，人工智能等课程中重要的分类算法。-K-nearest neighbor classification VC++, experimental data is the famous iris databases, data mining, machine learning, artificial intelligence courses classification algorithm.
nn
- 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
fcm
- fcm 聚类两个k近邻算法，k近邻的非正式描述，就是给定一个样本集exset，样本数为M，每个样本点是N维向量，对于给定目标点d，d也为N维向量，要从exset中找出与d距离最近的k个点(k<=N)，当k=1时，knn问题就变成了最近邻问-fcm cluster
Coordinate
- 基于R树的K近邻查询算法及递增的k近邻查询算法实现-the implemention of R-tree K-nearest neighbor query algorithm and incremental nearest neighbor query algorithm
wine_class
- 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.
floaterK1
- 这是用MTTLAB编程，采用K近邻法对提取的水面漂浮物特征进行分类-This is programming MTTLAB, K-nearest neighbor method floats feature to classify the extracted water
KNNC
- 使用K近邻算法分类的代码，可返回分类的识别率-KNN Classification
knnsearch
- 一个小而有效的程序来执行的K近邻搜索算法， 非常适合对K -近邻搜索算法的入学者。-A small but effective procedures to implement the K-nearest neighbor search algorithm is very suitable for K- nearest neighbor search algorithm admission
LDA
- LDA:线性判别分析方法。用于实现线性数据降维。采用K近邻分类器对数据进行分类-LDA: linear discriminant analysis method. Used to achieve linear data dimensionality reduction. Using K-nearest neighbor classifier for data classification
classifier
- 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.
recognition
- 一种加权K近邻语音情感识别程序，包括部分柏林语音情感库-A Weighting K-nearest neighbor speech emotion recognition program, including some libraries Berlin Speech Emotion
knn
- knn k近邻算法，可选择欧式距离或者曼哈顿距离-knn k nearest neighbor, Euclidean distance or Manhattan can choose the distance
Kjinlin
- K近邻c语言程序的简单应用 简单应用 -K-nearest neighbor c language program a simple application of a simple application of a simple application of a simple application
knn
- k近邻分类器分类 包括PCA功能 归一化 并且带有交叉检验功能-k nearest neighbor classifiers including PCA function normalized and with cross-validation function
lle
- LLE算法及改进的LLE算法，主要是对寻找K近邻时的欧式距离的改进-LLE algorithem and the improve_LLE agorithem，the process mainly improve the distance
KNN
- 机器学习K近邻分类算法，使用的是C++编程。如果一个样本在特征空间中的k个最相似(即特征空间中最邻近)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。-K-nearest neighbor classification machine learning algorithm, using the C++ programming. If a sample in feature space is k most similar (i.e., the feature space adjacent