Description: 此文件包含模式识别中一些经典的matlab代码，如：SVM、神经网络、最近邻等。-This file contains some of the classic pattern recognition matlab code, such as: SVM, neural networks, nearest neighbor and so on. Platform: |
Size: 786432 |
Author:王芝麻 |
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Description: 这是对于近邻法与支持向量机的ppt文件，能给学习神经网络方法的初学者帮助-This is the nearest neighbor and support vector machine ppt, learning neural network can give help for beginners Platform: |
Size: 8755200 |
Author:pakyongchan |
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Description: 关于metric learning的综述，涉及到许多的知识：SVM、kernel、SDP等-This paper surveys the field of distance
metric learning from a principle perspective, and includes a broad selection of recent work. In particular, distance metric learning is reviewed under different
learning conditions: supervised learning versus unsupervised learning, learning in a global sense versus in a local sense and the distance matrix based on linear kernel versus nonlinear kernel. In addition, this paper discusses a number of techniques
that is central to distance metric learning, including convex programming, positive semi-definite programming, kernel learning, dimension reduction, K Nearest Neighbor, large margin classification, and graph-based approaches. Platform: |
Size: 322560 |
Author:刘建飞 |
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Description: K近邻分类器，用于模式识别等领域，该程序短小精悍，适合与ANN和SVM进行比较研究，本人多篇论文用到，效果较好。-K-nearest neighbor classifier is often used in pattern recognition and other fields. It is suitful for a comparative study with ANN and SVM. I have published some papers used the code. The effect is good. Platform: |
Size: 1024 |
Author:XIAO |
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Description: 提出了一种基于DCT提取人脸特征技术和支持向量机分类模型的人脸识别方法。利用离
散余弦变换可提取人脸可识别的大部分信息,而支持向量机作为分类器,在处理小样本、高维数等
方面具有独特的优势,且泛化能力很强,无需先验知识。从ORL 人脸库上的实验结果可以看出,
DCT特征提取是很有效的,且SVM的分类性能优于最近邻分类器,同时提高了整个系统的运算速
度。-A face recognition method based on DCT for face feature extraction and support vector machine classification model. Can extract most of the information face recognition using discrete cosine transform and support vector machine as classifier, has unique advantages in dealing with small sample, high dimension and generalization ability, without prior knowledge. As can be seen from the experimental results on the ORL database DCT feature extraction is very effective, and the SVM classification performance better than the nearest neighbor classifier, while increasing the speed of operation of the entire system. Platform: |
Size: 354304 |
Author:罗朝辉 |
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Description: 清华模式识别第二次作业，采用dataset2.txt 数据作训练样本，采用身高与体重特征进行性别分类，建立最小错误贝叶斯分类器；2、采用身高体重数据作为特征，以 dataset2.txt 作为训练数据，用 Fisher 线性判别方法设计分类器；3、从多层感知器、SVM、近邻法选择一种方法，进行上述的分类实验；-Tsinghua second operation pattern recognition using dataset2.txt data for training samples, using height and weight characteristics of sex, to establish minimum error Bayesian classifier 2, using height and weight data as a feature to dataset2.txt as a training data, using Fisher linear discriminant analysis classifier design 3, from the MLP, SVM, nearest neighbor method to choose a method of classification of the above experiments Platform: |
Size: 7168 |
Author:zhusy09 |
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Description: 基于词袋的场景分类，分类器采用SVM和最近邻，需要vlfeat和图片见http://cs.brown.edu/courses/csci1430/proj3/-Based on word bag scene classification, SVM classifier using the nearest neighbor and need vlfeat and pictures see http://cs.brown.edu/courses/csci1430/proj3/ Platform: |
Size: 1201152 |
Author:yeon |
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Description: 这是天津大学胡清华老师在粗糙集邻域领域做的最经典的源码，同学们可以在此基础上学习和修改，入口程序已经写好，需要其他方法可以自己添加，MAIN.m是入口程序，参数的意思在子函数里讲的很明白，调用了featureselect_FW_fast.m用来属性约简，几个clsf_dpd文件是使用不同的距离公式来计算属性重要度，选择得到属性结果，使用crossvalidate.m十折交叉算法来计算计算算法精度，该段代码调用了几个分类器，C4_5.m是决策树，KNN.m是最近邻分类器，NEC.m是类似于KNN的胡修改的程序，osu_svm3.00文件夹是使用svm分类器调用的文件，使用该分类器时，代码中间的路径需要修改。另外附上一堆常用的数据集。-This is Hu Qinghua teacher at Tianjin University neighborhood rough set field do the most classic source code, students can learn and modify On this basis, the entry procedures have been written, you need other ways to add your own, MAIN.m entry program is meaning parameters Functions talked in very clear call for the featureselect_FW_fast.m attribute reduction, several clsf_dpd file is to use a different formula to calculate the distance attribute importance, choose properties to get the results, use crossvalidate.m ten fold cross algorithm to calculate the accuracy of the calculation algorithm, the segment code calls several classifiers, C4_5.m is a decision tree, KNN.m is the nearest neighbor classifier, NEC.m is similar to KNN Hu modified program, osu_svm3. 00 folders using svm classifier called file, using the classification code in the middle of the path need to be modified. Also attach a bunch of common data sets. Platform: |
Size: 2542592 |
Author:robert |
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Description: 本书第一部分主要介绍机器学习基础，以及如何利用算法进行分类，并逐步介绍了多种经典的监督学习算法，如k近邻算法、朴素贝叶斯算法、Logistic回归算法、支持向量机、AdaBoost集成方法、基于树的回归算法和分类回归树（CART）算法等。第三部分则重点介绍无监督学习及其一些主要算法：k均值聚类算法、Apriori算法、FP-Growth算法。第四部分介绍了机器学习算法的一些附属工具。-
In the first part, mainly introduced the machine learning base, and how to use the algorithm to classify, and gradually introduced the variety of classical supervised learning algorithms such as k-nearest neighbor, naive Bayes algorithm, logistic regression algorithm, support vector machine (SVM) and AdaBoost ensemble method, based on the regression tree algorithm and classification and regression tree (CART) algorithm. The third part focuses on unsupervised learning and some of the main algorithms: K mean clustering algorithm, Apriori algorithm, FP-Growth algorithm. The fourth part introduces some tools of machine learning algorithm. Platform: |
Size: 20149248 |
Author:孙伟 |
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Description: 本文件是图像场景识别并进行分类的程序，已运行成功。
分别利用1 tiny image描述和最近邻分类器
2 bags of sifts描述和最近邻分类器
3bags of sifts描述和线性svm分类器进行场景分类识别的。
在主程序proj3中将FEATURE 改成tiny image，CLASSIFIER 改成nearest neighbor，注释其他FEATURE 和CLASSIFIER的选择就可以实现第一种场景分类识别：tiny image描述和最近邻分类器。以此类推就可以依次改FEATURE 和CLASSIFIER 形成第二种情况：bags of sifts描述和最近邻分类器和第三种情况：bags of sifts描述和线性svm分类器进行场景分类识别。(This document is an image scene recognition and classification of procedures have been run successfully.) Platform: |
Size: 18185216 |
Author:wujie123 |
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Search - SVM and Nearest Neighbor