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knn.rar
- k-nn算法实现分类，模式识别作业，分三类，75个训练集，25个测试集，输出对测试集分类的结果,k-nn classification algorithm, pattern recognition operations are classified into three types, 75 training sets, 25 test set, the output of the test set classification results
parzen
- 这是一个模式识别中的parzen窗的一个简单仿真分类实例，其中female.txt和male.txt是训练样本，test.txt是测试样本，分类效果非常好，对于模式学习的初学者将会有很大帮助。-This is a pattern recognition in a simple window parzen Category simulation examples, one of female.txt and male.txt training samples, test.txt is the me
Games
- Bayes分类器——算法设计 1． 使用决策树(Decision tree)分类算法、朴素贝叶斯（Naï ve Bayes）算法或者K-近邻（kNN）算法（三者任选其一）对给定的训练数据集构造分类器，并在测试数据集上进行分类预测。 2． 数据集描述： Tic-tac-toe游戏的二叉分类。Tic-tac-toe游戏示例如下-Bayes classifier- Algorithm 1. Using the decision tree (Decision tree) classi
co-training
- 半监督学习co-training 回归算法的java代码实现。-COREG is a co-training style semi-supervised regression algorithm, which employs two kNN regressors using different distance metrics to select the most confidently labeled unlabeled examples for each other.
Chinese-text-categorization-Study
- 本文通过对Bayes、KNN、SVM 应用于中文文本分类进行比较实验研究。 应用ICTCLAS 对中文文档进行分词，在大维数，多数据情况下应用TFIDF 进行 特征选择，并同时利用它实现了对特征项进行加权处理，使文本库中的每个文本 具有统一的、可处理的结构模型。然后通过三类分类算法实现了对权值数据进行 训练和分类。-Based on the Bayes, KNN, SVM applied to compare the Chinese text ca
lab02
- 在MATLAB实现的用C实现的KNN算法，输入训练数据文件，和test文件，进行预测分类，并且可以与真实情况比较测试预测正确百分比-Implemented in MATLAB KNN algorithm implemented in C, the input training data file, and test files, to predict the classification and testing with the real situation is more correct pe
SOMface_demo
- 基于自组织神经网络的人脸识别代码 X.Tan, S.Chen, Z.-H. Zhou, and F. Zhang, Recognizing Partially Occluded, Expression Variant Faces from Single Training Image per Person with SOM-Based kNN Ensemble. IEEE Transactions on Neural Networks.2005, 16(4): 875-886.-X.Tan,
KNN-Face-Recognition
- KNN分类算法实现人脸识别，数据集为ORL。训练样本分别为2、4、6，其余为测试样本。-KNN classification algorithm for face recognition, the data set for the ORL. 2,4,6 training samples respectively, the rest of the test samples.
KNN
- 这是自己编的用KNN方法对产生的高斯数据进行分类的MATLAB程序，里面有高斯训练及测试数据的产生，还有分类，程序里有注释-This is their series with the KNN method to classify the Gaussian data generated MATLAB program, which has produced a Gaussian training and test data, as well as classification, program an
KNN
- Performs KNN classification to a set of data points using a given training data and the associated class labels
KNN
- 本例程是一个完整的学习KNN算法的工程，使用VS2010+C#编程,含训练数据及测试数据-This routine is a complete learning KNN algorithm works using VS2010+ C# programming, including training data and test data
KNN
- KNN近邻算法分类程序,包含训练数据和测试数据.-KNN classification procedures, including training and testing data.
knn
- KNN算法的matlab实现，包含main文件和训练样本-KNN algorithm matlab implementation, including the main documents and training samples
KNN算法代码（matlab）
- 本实验中的KNN分类算法采用Matlab语言实现。 主函数“knnClass.m”读取训练和测试的数据文件，然后调用knn函数进行分类运算，并使用图像的形式将分类结果显示出来。(The KNN classification algorithm in this experiment is realized by Matlab language. The main function "knnClass.m" reads the training and test data fil
knn-MATLAB
- 这是一个实现简单的多数表决法的KNN算法。KNN算法涉及三个重要的步骤，分别是决定K的大小；距离的表达方法（一般有欧式距离，曼哈顿距离，Minkowski距离）；决策方法（多数表决法，KD树法等）。本程序是采用多数表决的决策方法，距离表达采用欧式距离。适用于小样本少特征的数据集。(KNN algorithm realized by MATLAB, useful for small training set and less features.)
KNN
- 在训练集中数据和标签已知的情况下，输入测试数据，将测试数据的特征与训练集中对应的特征进行相互比较，找到训练集中与之最为相似的前K个数据，则该测试数据对应的类别就是K个数据中出现次数最多的那个分类。(In the case where the training data and the tag are known, the test data is input, the characteristics of the test data are compared with the character
knn
- k最近邻算法:分类和回归。通过对训练集分类训练模型，验证集用于验证数据的准确性。(K nearest neighbor algorithm: classification and regression. Through the training set classification training model, the verification set is used to verify the accuracy of the data.)
KNN分类器
- 一、用python或matlab编写一个KNN分类器 训练集为semeion_train.csv（手写体识别） 测试集为semeion_test.csv 计算在测试集上错误率（k=1,k=3,k=5,k=10） ?(1. Write a KNN classifier with Python or matlab Training set is semeion_train.csv (handwriting recognition) The test set is semeion_test
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
KNN
- 一个简单好用的KNN算法程序，只需要输入训练集和对应的标签就可以得到想要的模型并进行测试集的预测(A simple and easy-to-use KNN algorithm program only needs to input the training set and corresponding tags to get the desired model and predict the test set)