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是支持向量机工具箱（matlab），可用于模式分类，模式识别等。-support vector machines Toolbox (Matlab), can be used for pattern classification, pattern recognition.
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一个模式分类的工具箱，matlab语言实现，对模式识别相关方向的人很有用-pattern classification of a toolbox, Matlab language, pattern recognition related to the direction of useful
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The MatClass IV Toolbox for MatLab has been developed to support experiments
on feature based classification problems.
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这是一些关于模式识别工具箱的源代码,和模式识别第二版配套使用，有很强的运用价值。,These are some original Matlab codes on pattern classification:pattern calssification toolbox
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一个matlab平台应用的svm工具箱，该工具箱包括了二种分类,二种回归,以及一种一类支持向量机算法-A matlab platform applications svm toolbox, the kit includes two kinds of classification, two kinds of return, and a one-class support vector machine algorithm
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MOLMAP multiway toolbox是一个matlab集成工具箱，用来计算分子的MOLMAP得分，并将其用于后续的回归或分类模型中。-The MOLMAP multiway toolbox is a collection of MATLAB modules for calculating MOLMAP scores on multiway data. The scores can be used in subsequent regression or classification mo
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支持向量机工具箱一种，主要解决分类和回归等问题，它是在matlab环境下运行的。-A Support Vector Machine Toolbox, mainly to resolve issues such as classification and regression, which is running in the matlab environment.
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介绍数字滤波器的定义、分类及实现方法。讨论IIR滤波器、FIR滤波器的设计方法以及如何运用MATLAB中的DSP Blockset工具箱设计数字滤波器。-Introduce digital filter definition, classification and realization method. Discussion of IIR filters, FIR filter design methods and how to use MATLAB in the DSP Blockset to
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svm工具箱，应用于matlab平台，给出了C_SVC二类分类算法的历程-svm toolbox, used matlab platform, given C_SVC the course of second-class Classification Algorithm
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matlab仿真例程，是支持向量机工具箱（matlab），可用于模式分类，模式识别 Nu_SVC二类分类算法-matlab simulation routines, support vector machine toolbox (matlab), can be used for pattern classification, pattern recognition Nu_SVC second-class Classification Algorithm
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Gradient information serves several purposes. It can relate
the structure of objects in an image, identify features of interest
for recognition/classification directly or provide the basis of further
processing for various computer vision
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WINDOWS操作系统下MATLAB图像处理工具箱，非常好用-Matlab demo-Image processing toolbox
- Texture Segmentation Using Texture Filte
(entropyfilt)
- color-Based Segmentation Using K-Means Clustering
Vgg-matlab
Zisserman: Texture Classification: Are Filt
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由于libsvm的matlab版本的工具箱libsvm-mat并没有给出寻参的函数模块，而无论利用libsvm工具箱进行分类还是回归，参数的选取是十分重要的，鉴于此libsvm-mat-2.89-3[FarutoUltimate3.0]在
libsvm-mat-2.89-3的基础上给出相应的辅助函数插件，方便用户来选取最佳的参数，现对该工具箱里主要的辅助函数插件的接口进行介绍。-As the matlab version of the toolbox libsvm libsvm-mat
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采用matlab的神经网络工具箱对故障进行分类-Matlab neural network toolbox used for fault classification
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These MATLAB functions were created for use in the generation,
classification and manipulation of Costas arrays. The code was
created and is maintained by Ken Taylor, Konstantinos Drakakis
and Scott Rickard.
For more information
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matlab的模式分类工具箱，包含大量模式识别的经典算法。-The matlab pattern classification toolbox contains a large number of classic pattern recognition algorithms.
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最小冗余最大相关性（MRMR）（MRMR.M）
需要外部库。详情请见MRMR。下载一个更新版本的互信息工具箱
偏最小二乘（PLS）回归系数（ReGCOEF.m）
使用MATLAB统计工具箱中的PLSReress
ReliefF（分类）和RReliefF（回归）（ReleFracePr.M.）
从Matlab STATS工具箱中包装Releff.m。这是Matlab R2010B以后提供的。
ReliefF的另一个选择是使用ASU特征选择工具箱中的代码。这使用WEKA
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PSO-LSSVM分类测试程序代码模板,PSO优化LSSVM工具箱——分类部分(PSO-LSSVM Classification Test Program Code Template, PSO Optimizing LSSVM Toolbox-Classification Part)
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使用matlab2019a深度学习工具箱实现的CNN卷积神经网络分类例程，数据是随机生成的一维随机数(Using the CNN convolution neural network classification routine realized by MATLAB 2019a deep learning toolbox, the data is one-dimensional random number generated randomly)
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使用Matlab深度学习工具箱-googlenet 图像分类(Using GoogLeNet to classify images using deep learning toolbox)
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