搜索资源列表
stprtool.rar
- 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines,
svm
- svm is a classifier.SUPPORT VECTOR MACHINE is used for train and classify new datas based on training
K-Fold_CV_Tool
- MATLAB cross-validation tool for classification and regression v0.1 FEATURES: + K-fold cross validation. + Arbitrary train and prediction functions with parameters can be used. + Arbitrary loss function can be used. + Wrappers for
svm_train
- 支持向量机训练，可根据自己的情况进行修改-SVM train
svm-train
- emd分解，近似阈的信号svm检测和训练-training of svm
basic-SVM_Indian_pines
- svm_进行indian_pines数据集合分类。-use svm to classify the indian_pines data with train and test data in the rar
jesxkbjv
- 包括脚本文件和函数文件形式，包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法，保证准确无误，是学习通信的好帮手，包括最小二乘法、SVM、神经网络、1_k近邻法,LCMV优化设计阵列处理信号，相参脉冲串复调制信号，对信号进行频谱分析及滤波，采用的是脉冲对消法。- Including scr ipt files and function files in the form, Including the MUSIC algorithm, ESPRIT algorithm ROOT-MU
SVMTrain
- svm train in pattrn recognition domain
svmtrain
- svm的训练函数 dtgd所得过封侯换个房间后(train ghjghk cfhfgj ghg gjyhk hjhkh hjkhkm)
SVM
- 运用SVM训练分类,并给出标准化以及网络搜索方法确定SVM各参数(use SVM to train and classify samples)
FeatureExtractionUsingAlexNetExample
- 本示例展示了怎样从一个预处理的卷积神经网络中提取特征，并用这些特征去训练一个图像分类器。(This example shows how to extract learned features from a pretrained convolutional neural network, and use those features to train an image classifier. Feature extraction is the easiest and fastest way use
SVM
- 该算法用Visual Studio编写 ，用于实现对样本的训练以及测试，并可以转换成matlab语言，直接调用子程序(The algorithm is written in Visual Studio, which is used to train and test the sample, and can be converted into a matlab language and directly invoked the subroutine.)
PCA+SVM
- 采用经典的ORL人脸数据集，利用PCA进行进行降维，然后用SVM进行数据集的分类和训练。上传文件内包含libSVM3.2安装包(The classical ORL face dataset is used for dimension reduction by PCA, and then SVM is used to classify and train the dataset.)
植物虫害检测（GUI，注释，svm算法）
- 植物虫害检测（GUI，注释，svm算法） 该课题为基于MATLAB SVM方法的植物病害检测系统，带GUI界面，可以识别多种被虫害侵蚀的植物叶子，输出结果。带论文和详细注释。 train 对黄瓜子文件夹所有图片提取 颜色矩特征和gabor纹理特征，然后svm训练 test 对测试图像灰度化，滤波，提取 颜色矩特征和gabor纹理特征，然后svm模型测试，输出类别 colorMom.m 颜色矩特征提取 Gabor_palm.m gabor纹理特征提取(Plant pe