搜索资源列表
KNN
- K最邻近密度估计分类,K最邻近密度估计技术是一种分类方法,不是聚类方法。-K nearest neighbor classification density estimation, K nearest neighbor density estimation technique is a classification method, not the clustering method.
KNN-and-fisher-
- 最近邻和fisher分类matlab代码-Nearest neighborand and fisher classification matlab code
llde_cmb
- 人脸检测一直是人们在研究的问题,流形学习用于人脸检测中的特征提取,用PCA与constructM进行降维,KNN分类器用于分类。取得非常好的效果。-Face detection has been the problem of people in the study, manifold learning for face detection feature extraction using PCA and constructM dimension reduction, KNN classifier
knn
- knn算法的简单实现,需要测试两个文件,一个测试文档,一个是待分类文本-knn algorithm is simple to achieve, you need to test the two documents, a test document, a text is to be classified
knn-softsvm-matlab
- matlab的knn网络,最小二乘算法,softsvm分类器实现,以及简单的交叉验证等,三种产检的方法-knn,softsvm matlab
KNN
- 基于PCA降维的KNN,最近邻分类matlab实现。-PCA dimensionality reduction based the KNN, the nearest neighbor classification matlab.
LDA
- example: 演示程序 creatData:生成数据 creatTrainLabelMat:生成数据标签 LDA:提取fisherface knnRecognition:knn分类器 knnsearch:knn搜索-example: demo creatData: generate data creatTrainLabelMat: generating data label LDA: Extract fisherface knnRecogni
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
KNNDriver
- 基于Hadoop的KNN分类算法,在MapReduce框架下编写,集群环境下调试成功。-KNN classification algorithm based on Hadoop, MapReduce framework under preparation, cluster environment debugging success.
JSvmLib
- SVM的java算法实现。可以跑通。support vector manchine and kNN分类的源代码.支持向量机是数据处理的比较良好的方法-The java SVM algorithm. You can run through.
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
KNN
- KNN算法实现 文本分类,C++实现-KNN text classification
knn
- knn经典分类器 使用matlab实现可以直接使用-knn classifican
knn
- 分别利用java和C++实现的KNN文本分类算法,每个程序模块都有详细注释-Respectively, the use of java and C++ implementation of KNN text classification algorithm, each program module has detailed notes
KNN(CSHARP)
- KNN算法在进行字典中词分类的算法实现,有例子,很详尽-KNN algorithm
knn
- K近邻(KNN):分类算法KNN是non-parametric分类器(不做分布形式的假设,直接从数据估计概率密度),是memory-based learning KNN不适用于高维数据(curse of dimension)-K-Nearest Neighbor (KNN): Classification Algorithm. KNN is a non-parametric classifiers (not to assume that the distribution of forms, fr
Bag-of-visual-words
- SIFT等局部特征的词袋模型实现。包括K-means聚类,直方图特征的形成,以及KNN分类。-SIFT local features such as word bag model implementation. Including K-means clustering to form histogram features, and KNN classification.
knn
- 简单的 knn 文本算法 ,用于中文文本分类,比较方便的方法!-Simple text knn algorithm for Chinese text classification, more convenient way!
DataMiningClassify
- 数据挖掘分类算法,依次执行数据预处理、朴素贝叶斯分类、KNN分类-classify algorithm for data mining.It contains data preprocess、Bayes classification and KNN classification.
LDA_KNN_OA
- KNN是有监督的分类算法,将测试点归类为其K个进邻点中出现次数最多的类别。KNN_Cla 1.利用所有带标记的数据作为train数据,调用KNN分类函数KNN_Cla()对整个图像进行分类,得到整个图像的分类结果图。 2.随机在所有带标记的数据中选择train和test数据(50 train数据,50 test数据)然后进行kNN分类。随机选择10次,计算总体分类精度OA,然后求平均结果,作为最终对算法的评价。K值依次选择1,3,5,7,9,11,分别用这6种K的取值进行kNN算法