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Description: LISTVIEW + DATABASE PROGRAMMING FUNCTIONS IN A NUTSHELL This solution contains a classLibrary project and a WindowsApplication project. The classlibrary project has only one class which has almost all the necessary functions and subs one may need during programming with a listview. -LISTVIEW DATABASE PROGRAMMING FUNCTIONS IN A NUTSHELL This solution contains a classLib rary WindowsApplication project and a project . The classlibrary project has only one class wh ich has almost all the necessary functions and s ubs one may need during programming with a listv iew.
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Author: 微环境 |
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Description: LIBSVM源码。LIBSVM 是台湾大学林智仁(Chih-Jen Lin)博士等开发设计的一个操作简单、
易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、
n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）
等问题，提供了线性、多项式、径向基和S形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。
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Author: 刘铁军 |
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Description: LIBSVM 是台湾大学林智仁(Chih-Jen Lin)博士等开发设计的一个操作简单、
易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、
n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）
等问题，提供了线性、多项式、径向基和S形函数四种常用的核函数供选择，可
以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概
率估计等.
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Size: 566248 |
Author: 327457572@qq.com |
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Description: LISTVIEW + DATABASE PROGRAMMING FUNCTIONS IN A NUTSHELL This solution contains a classLibrary project and a WindowsApplication project. The classlibrary project has only one class which has almost all the necessary functions and subs one may need during programming with a listview. -LISTVIEW DATABASE PROGRAMMING FUNCTIONS IN A NUTSHELL This solution contains a classLib rary WindowsApplication project and a project . The classlibrary project has only one class wh ich has almost all the necessary functions and s ubs one may need during programming with a listv iew.
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Size: 64512 |
Author: 微环境 |
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Description: LIBSVM源码。LIBSVM 是台湾大学林智仁(Chih-Jen Lin)博士等开发设计的一个操作简单、
易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、
n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）
等问题，提供了线性、多项式、径向基和S形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。-LIBSVM source. LIBSVM is林智仁Taiwan University (Chih-Jen Lin) Dr. develop design a simple, easy to use, fast and effective generic SVM software package, can solve the classification problems (including the C-SVC, n- SVC), regression ( including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and so on, provides a linear, polynomial, radial basis function and the S-shaped kernel function of four commonly used for selection, can effectively to solve a wide range of issues, cross-validation to choose the parameters of the imbalance in the weighted sample, multi-category probability estimation.
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Author: 刘铁军 |
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Description:
LIBSVM 是台湾大学林智仁 (Chih-Jen Lin) 博士等开发设计的一个操作简单、易于使用、快速有效的通用 SVM 软件包，可以解决分类问题（包括 C- SVC 、n - SVC ）、回归问题（包括 e - SVR 、 n - SVR ）以及分布估计（ one-class-SVM ）等问题，提供了线性、多项式、径向基和 S 形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。-LIBSVM is林智仁Taiwan University (Chih-Jen Lin) Dr. develop design a simple, easy to use, fast and effective generic SVM software package, can solve the classification problems (including the C-SVC, n- SVC), regression ( including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and so on, provides a linear, polynomial, radial basis function and the S-shaped kernel function of four commonly used for selection, can effectively to solve a wide range of issues, cross-validation to choose the parameters of the imbalance in the weighted sample, multi-category probability estimation.
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Author: 小潘 |
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Description: svm Main_SVM_One_Class 用于svm分类的 在matlab中运用 -svm classification svm Main_SVM_One_Class for use in matlab
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Author: 丛宽 |
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Description: LIBSVM 是台湾大学林智仁(Chih-Jen Lin)博士等开发设计的一个操作简单、易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）等问题，提供了线性、多项式、径向基和S形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。
2.89版本是09年刚更新的一个版本。-LIBSVM
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Author: woyaofei |
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Description:
c# 写的一个http 端口监听 类
用于监听 一些网外通讯端口 达到控制效果-
this is one class which i use c# write,
it s a listener
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Author: 陆晓峰 |
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Description: 本文的目的是设计一个完成URL编码的C++类。在我曾经的项目中，我需要从VC++ 6.0应用程序中POST数据，而这些数据需要进行URL编码。我在MSDN中查找能根据提供的字符串生成URL编码的相关类或API，但我没有找到，因此我必须设计一个自己的URLEncode C++类。-The purpose of this paper is to design a complete URL-encoded C++ classes. I have a project, I need VC++ 6.0 application, POST data, and these data need to be URL encoded. I have MSDN to find a string generated according to URL encoding to provide the relevant class or API, but I did not find, so I have to design one' s own URLEncode C++ classes.
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Author: mxb |
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Description: -s svm类型：SVM设置类型(默认0)
0 -- C-SVC
1 --v-SVC
2 – 一类SVM
3 -- e -SVR
4 -- v-SVR
-t 核函数类型：核函数设置类型(默认2)
0 – 线性：u v
1 – 多项式：(r*u v + coef0)^degree
2 – RBF函数：exp(-r|u-v|^2)
3 –sigmoid：tanh(r*u v + coef0)
-d degree：核函数中的degree设置(针对多项式核函数)(默认3)
-g r(gama)：核函数中的gamma函数设置(针对多项式/rbf/sigmoid核函数)(默认1/ k)
-r coef0：核函数中的coef0设置(针对多项式/sigmoid核函数)((默认0)
-c cost：设置C-SVC，e -SVR和v-SVR的参数(损失函数)(默认1)
-n nu：设置v-SVC，一类SVM和v- SVR的参数(默认0.5)
-p p：设置e -SVR 中损失函数p的值(默认0.1)
-m cachesize：设置cache内存大小，以MB为单位(默认40)
-e eps：设置允许的终止判据(默认0.001)
-h shrinking：是否使用启发式，0或1(默认1)
-wi weight：设置第几类的参数C为weight*C(C-SVC中的C)(默认1)
-v n: n-fold交互检验模式，n为fold的个数，必须大于等于2--s svm_type : set type of SVM (default 0)
0-- C-SVC
1-- nu-SVC
2-- one-class SVM
3-- epsilon-SVR
4-- nu-SVR
-t kernel_type : set type of kernel function (default 2)
0-- linear: u *v
1-- polynomial: (gamma*u *v+ coef0)^degree
2-- radial basis function: exp(-gamma*|u-v|^2)
3-- sigmoid: tanh(gamma*u *v+ coef0)
4-- precomputed kernel (kernel values in training_instance_matrix)
-d degree : set degree in kernel function (default 3)
-g gamma : set gamma in kernel function (default 1/k)
-r coef0 : set coef0 in kernel function (default 0)
-c cost : set the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1)
-n nu : set the parameter nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5)
-p epsilon : set the epsilon in loss function of epsilon-SVR (default 0.1)
-m cachesize : set cache memory size in MB (default 100)
-e epsilon : set tolerance of termination criterion (default 0.001)
-h shrinking: whether to use the shrinking heuristics, 0 or 1 (default 1)
-b
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Author: little863 |
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Description: function [L,C] = kmeans(X,k)
KMEANS Cluster multivariate data using the k-means++ algorithm.
[L,C] = kmeans(X,k) produces a 1-by-size(X,2) vector L with one class
label per column in X and a size(X,1)-by-k matrix C containing the
centers corresponding to each class.
Version: 07/08/11
Authors: Laurent Sorber (Laurent.Sorber@cs.kuleuven.be)
References:
[1] J. B. MacQueen, "Some Methods for Classification and Analysis of
MultiVariate Observations", in Proc. of the fifth Berkeley
Symposium on Mathematical Statistics and Probability, L. M. L. Cam
and J. Neyman, eds., vol. 1, UC Press, 1967, pp. 281-297.
[2] D. Arthur and S. Vassilvitskii, "k-means++: The Advantages of
Careful Seeding", Technical Report 2006-13, Stanford InfoLab, 2006.
-function [L,C] = kmeans(X,k)
KMEANS Cluster multivariate data using the k-means++ algorithm.
[L,C] = kmeans(X,k) produces a 1-by-size(X,2) vector L with one class
label per column in X and a size(X,1)-by-k matrix C containing the
centers corresponding to each class.
Version: 07/08/11
Authors: Laurent Sorber (Laurent.Sorber@cs.kuleuven.be)
References:
[1] J. B. MacQueen, "Some Methods for Classification and Analysis of
MultiVariate Observations", in Proc. of the fifth Berkeley
Symposium on Mathematical Statistics and Probability, L. M. L. Cam
and J. Neyman, eds., vol. 1, UC Press, 1967, pp. 281-297.
[2] D. Arthur and S. Vassilvitskii, "k-means++: The Advantages of
Careful Seeding", Technical Report 2006-13, Stanford InfoLab, 2006.
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Author: ehsan |
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Description: This a simple on one checkers game all within one class for simplification. It s made this way so that anybody can make changes and make it their own.-This is a simple one on one checkers game all within one class for simplification. It s made this way so that anybody can make changes and make it their own.
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Author: Buddy |
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Description: C++经典语法与应用，类的编写与应用，构造与析构函数，函数的重载，类的继承，函数覆盖，基类与派生类的构造函数、析构函数先后调用顺序，如何在派生类构造函数中向基类的构造函数传递参数，this成员变量，类型转换的内幕，虚拟函数与多态性,引用和指针变量的区别与共同处。VC工程的编译原理与过程，将工程中不同的类拆分到不同的文件中，每一个类由一个.h和.cpp文件共同完成，头文件重复定义问题的解决，培养了学员良好的编程习惯，也为以后分析MFC AppWizard生成的工程奠定了良好基础。-C++ classic grammar with application class writing with the application, the constructor and destructor function, the function of the overloaded class inheritance, function coverage, the base class and the derived class s constructor, destructor has invoked the order, how in the derived classthe parameters passed to the constructor of the base class constructor, the this member variable of the insider type conversion, virtual functions and polymorphism, references and pointer variable distinction in common. VC compiler theory and engineering process, the different classes in the project is split into different files together to complete each one. H. Cpp file, header files define the solution of the problem is repeated, train students good programming habits, but also laid a good foundation for later analysis generated by the MFC AppWizard project.
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Author: 张媛媛 |
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Description: SVM平台，操作简单、易于使用的通用SVM 软件包，可以解决分类问题（包括C- SVC、n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）等问题，提供了线性、多项式、径向基和S 形函数四种常用的核函数供选择。-SVM platform is a simple, easy to use, versatile SVM software package can solve classification problems (including C-SVC, n- SVC), regression (including e- SVR, n- SVR) and distribution estimation (one-class-SVM) and other issues, providing a linear, polynomial, radial basis functions and the S-shaped four commonly used kernel functions for selection.
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Author: 凡轩 |
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Description: PDF s for building one s knowlege in the field of Digital Image Processing
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Author: Gaurav |
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Description: 自动生成数据库的结构类，每一个库对应生成一个类-Automatic generation of structural class s, one for each library to generate a class
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Author: youname |
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Description: esh generation is one of the most critical aspects of engineering simulation. Too many cells may result in long solver runs, and too few may lead to inaccurate results. ANSYS Meshing technology provides a means to balance these requirements and obtain the right mesh for each simulation in the most automated way possible. ANSYS Meshing technology has been built on the strengths of stand-alone, class-leading meshing tools. The strongest aspects of these separate tools have been brought together in a single environment to produce some of the most powerful meshing available.
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Author: charukesh |
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Description: 创建一个People类，定义成员变量如编号、姓名、性别、年龄；定义成员方法“获得编号”、“获得姓名”、“获得年龄”等，再创建People类的对象-create a class of people,own one person s age,name and number
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Author: shirley |
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Description: When extracting discriminative features multimodal
data, current methods rarely concern the data distribution.
In this paper, we present an assumption that is consistent with
the viewpoint of discrimination, that is, a person’s overall
biometric data should be regarded as one class in the input space,
and his different biometric data can form different Gaussians
distributions, i.e., different subclasses. Hence, we propose a novel
multi-modal feature extraction and recognition approach based
on subclass discriminant analysis (SDA). Specifically, one
person’s different bio-data are treated as different subclasses of
one class, and a transformed space is calculated, where the
difference among subclasses belonging to different persons is
maximized, and the difference within each subclass is minimized.
Then, the obtained multi-modal features are used for
classification. Two solutions are presented to overcome the
singularity problem encountered in calculation, which are using
PCA preprocessing,-When extracting discriminative features multimodal
data, current methods rarely concern the data distribution.
In this paper, we present an assumption that is consistent with
the viewpoint of discrimination, that is, a person’s overall
biometric data should be regarded as one class in the input space,
and his different biometric data can form different Gaussians
distributions, i.e., different subclasses. Hence, we propose a novel
multi-modal feature extraction and recognition approach based
on subclass discriminant analysis (SDA). Specifically, one
person’s different bio-data are treated as different subclasses of
one class, and a transformed space is calculated, where the
difference among subclasses belonging to different persons is
maximized, and the difference within each subclass is minimized.
Then, the obtained multi-modal features are used for
classification. Two solutions are presented to overcome the
singularity problem encountered in calculation, which are using
PCA preprocessing,
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Author: avinash trivedi |
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