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KNN DEMO This is a binary classification problem defined on a N*N field.
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在matlab环境下，利用bp神经网络实现异或分类问题,In the matlab environment, the use of bp neural network XOR classification problem
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这是一个用vc++写成的有关SVM分类的问题，能进行多类分类。找最优超平面相当好。十分有用-This is a used vc++ Written on the SVM classification problem, able to multi-category classification. To find optimal hyper-plane is very good. Very useful
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SVDD的工具箱，可以很好的处理一类分类问题，详见Support Vector Data Descr iption一文-SVDD tools，can be used to process one class classification problem,for more details ,we refer to "Support Vector Data Descr iption"
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AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files
1. ADABOOST_tr.m
2. ADABOOST_te.m
to traing and test a user-coded learnin
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pattern recognition中多类分类问题的GAMLS通用学习系统框架-pattern recognition in the multiclass classification problem GAMLS Universal Learning System Framework
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纠错输出编码SVM算法，解决多类分类问题-Error-correcting output coding SVM algorithm, to solve multiclass classification problem
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一、问题描述若要在n个城市之间建役通信网络，只福要架设n-1条级路即可．如何以最低的经济代价建设这个通信网，是一个网的最小生成树问题。二、基本要求 （1）利用克鲁斯卡尔算法求图的最小生成树。 （2）能实现教科书6.5节中定义的抽象数据类型MFSet.以此表示构造生成树过程中的连通分量。 (3 ) 以文本形式输出生成树中各条边以及他们的权值．三、需求分析 1、构造图结构。 2、利用克鲁斯卡尔算法求图的最小生成树。 3、完成生成树的输出。 -I. Descr iption of the proble
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基于混合算法的均衡路程MTSP研究
给出了MTSP的整数线性规划模型、分类, 提出了均衡各旅行商访问路程和均衡各旅行商访问人数的多目标
问题针对均衡各旅行商访问路程的设计了相应的求解算法, 求解算法为遗传算法和一的混合算法给出了相应
的示例和实验结果, 并对实验结果的有效性进行了研究-Hybrid algorithm based on a balanced study of MTSP given distance of the MTSP integer linear programm
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This the program for the multi classification problem utiizing the incremental support vector domain density descr iption method.-This is the program for the multi classification problem utiizing the incremental support vector domain density descr ip
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BP算法在非线性分类问题中的简单应用，三层BP网络！-BP algorithm in non-linear classification problem in a simple application of three-layer BP network!
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ROC curves illustrate performance on a binary classification problem where classification is based on simply thresholding a set of scores at varying levels. Lenient thresholds give high sensitivity but low specificity, strict thresholds give high spe
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Learning to Rank的一个方法，把排序问题转换成了一个分类问题，然后用支持向量机（SVM）训练出一个模型来。-Learning to Rank of a way to sort problem is transformed into a classification problem, and then use support vector machine (SVM) to train a model.
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SVM方法的基本思想是：定义最优线性超平面，并把寻找最优线性超平面的算法归结为求解一个凸规划问题。进而基于Mercer核展开定理，通过非线性映射φ，把样本空间映射到一个高维乃至于无穷维的特征空间（Hilbert空间），使在特征空间中可以应用线性学习机的方法解决样本空间中的高度非线性分类和回归等问题。svm 程序，即支持向量机的代码。-The basic idea of SVM method are: the definition of the optimal linear hyperplane,
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A basic PCA classifier is provided here for a two class classification problem.
An example is given, with some multimodal MRI scans from Multiple Sclerosis patients, in which the brain lesions of two patients are annotated and in the third are dete
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The sample application is able to perform both Classification and Regression using Support Vector Machines. It can read Excel spreadsheets and determines the task to be performed depending on the number of the columns in the sheet. If the input table
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bp算法（误差反传算法） 解决分类问题
通过一层输入，一层输出 和一个隐层-bp algorithm (error back propagation algorithm) to solve the classification problem by a layer of input, output, and a hidden layer
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k均值算法是模式识别的聚分类问题，这是用C#实现其算法-K-means algorithm is pattern recognition of poly classification problem, this is written in c# realize its algorithm
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bp神经网络分类问题应用于识别四类语音信号-bp neural network classification problem applications
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The combination of Back Propagation Neural Network and Fuzzy Theory for Classification problem.
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