搜索资源列表
exclass1
- 支持向量机SVM和核函数的matlab实例-Examples of support vector machines SVM and kernel function matlab
sig
- 支持向量机SVM和核函数的matlab实例-Examples of support vector machines SVM and kernel function matlab
kernel-function
- 核函数的画法 包括全局核函数，局部核函数，分段核函数。-The painting of the kernel function including global nuclear function, local kernel function, segmented kernel function.
fastsvm1
- 机器学习大牛Dale Schuurmans写的多类SVMs的快速实现算法，可以自己修改核函数，通过K-fold cross validation训练得到最优参数，分类效果很好-Machine learning large cattle Dale Schuurmans write multi-class SVMs fast algorithm, can modify the kernel function, the optimal parameters through K-fold cross v
modkern
- Fortran实现多种常用stokes改化核函数的计算。-Fortran to achieve a variety of commonly used stokes conversion in the calculation of the kernel function.
libsvm-kernel--of-ploynomial-and-RBF
- 在libsvm平台下，用RBF核函数和polynomial多项式核函数结合，形成新的混合核函数，求验证其正确性-libsvm kernel of RBF and ploynomial
KPCA1
- 改程序为基于核函数的主成分分析算法的MATLAB实现程序,对于学习KPCA有很大帮助-This program is the MATLAB program which is based on the kernel principal component analysis
2
- 是关于神经网络的数据分类预测的一个源代码，关于向量机的，采用径向基核函数-Neural network data classification forecast
KPCA
- 本方法使用sprtool，介绍了Kpca的应用，来进行高位数据降维，介绍三种核函数的应用，并附有结果图。-This method uses sprtool, introduced Kpca applications for high data dimensionality reduction, introduced three nuclear function, together with the results in Fig.
duobu
- 多项式核函数的支持向量机作为模型预测的预测模型,多非线性系统进行多步模型预测控制-Polynomial kernel function as support vector machine model to predict the forecast model, nonlinear systems, multi-step model predictive control
fisher
- 实现基于核函数的Fisher分类器的算法-Fisher classification algorithm based on kernel function
0.5GP0.5S
- 支持向量机，不同核函数的混合来实现图像分割，以libsvm3.1工具箱为基础-Support Vector Machine
0.5PP0.5S
- 基于支持向量机的图像分割，以libsvm3.1工具箱为基础，用不同核函数的混合来实现图像分割，自己编的代码，并以成功运行-Based image segmentation based on support vector machine libsvm3.1 toolbox, with a mix of different kernel functions to achieve image segmentation, their compiled code to run successfully
GS
- 基于支持向量机的图像分割，以libsvm3.1工具箱为基础，用不同核函数的混合来实现图像分割，自己编的代码，并已成功运行-Based image segmentation based on support vector machine libsvm3.1 toolbox, with a mix of different kernel functions to achieve image segmentation, their compiled code to run successfully
PG
- 基于支持向量机的图像分割，以libsvm3.1工具箱为基础，用不同核函数的混合来实现图像分割，自己编的代码，并已成功运行-Based image segmentation based on support vector machine libsvm3.1 toolbox, with a mix of different kernel functions to achieve image segmentation, compiled code, and has been successfully
PS
- 基于支持向量机的图像分割，以libsvm3.1工具箱为基础，用不同核函数的混合来实现图像分割，自己编的代码，并已成功运行-Based image segmentation based on support vector machine libsvm3.1 toolbox, with a mix of different kernel functions to achieve image segmentation, compiled code, and has been successfully
Canny
- 利用Canny的方法实现边沿检测，核函数采用高斯核，sigma大小可以任意调节，阈值也可以任意选。界面优美。-Does the method of using Canny edge detection, the function USES the gaussian kernel, sigma size can be adjusted, and the threshold can be arbitrarily chosen. Beautiful interface.
gaussian_entropy
- 本算法利用高斯核函数对灰度图像进行增强，然后根据香农熵求出一个最佳阈值，利用该阈值进行分割。-This algorithm uses the Gaussian kernel enhanced gray image, and then an optimal threshold is obtained according to the Shannon entropy, the threshold segmentation.
Gabor
- 本算法可以在不同方向和不同尺度上对图像进行分析，利用高斯核函数对图像进行卷积，然后综合各个方向和尺度的数据的最大值，就可以得到理想的结果。该方法对冠脉造影图像中血管的分割效果比较好，无论主血管或是细小血管都比较好。-This algorithm can be analyzed in different directions and on different scales the image using the Gaussian kernel function of the image convo
svm方法步骤
- SVM方法最主要的工作是样本训练，获得训练模型参数。SVM中涉及大量的矩阵运算和推导，需要弄清楚，这样才能明白模型参数的含义，以便于判断当前选定的核函数是否合适。