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Description: 在SENSE成像中如何将中间图像转化为最终图像，就要用到这个程序-Using specfied sampling vector to generate a 2D aliasing matrix. The sampling vector is a vector of n-entries of either 0 or 1, where 0 indicates no k-space line acquisition and 1 indicates k-space line is acquired in the accelerated scan. For example, a sampling vector of [0 1 0 1 0 1 0 1 0 1] indicate the 2-fold acceleration with 8 phase encoding lines. The aliasing matrix is calculated based on Fourier imaging
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Size: 4096 |
Author: 李荣智 |
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Description: 简单SENSE图像重建，即使通过反傅里叶变换重建出最终图像-The data was acquired from 4-channel array coil using EPI sequence (2-shot, matrix: 64X64, TE: 50 ms) at a 1.5T scanner. The code estimates the coil sensitivity profiles directly from the image with anatomical contrast by low-pass smoothing. Subsequently, k-space data were decimated to simulate 2.0-fold acceleration (R=2.0). Finally, using least-squares estimate, the reconstructed full-FOV spin density image is obtained
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Size: 4096 |
Author: 李荣智 |
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Description: 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 KNN, SVM, GLM, robust regression and decision trees.
+ Wrappers for RMSE, MAD and misclassification loss functions.
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Size: 3072 |
Author: milk |
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Description: Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for the k-fold cross-validation of SVR. All the programs are flexible and could be implemented by the users themselves.-Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for the k-fold cross-validation of SVR. All the programs are flexible and could be implemented by the users themselves.
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Size: 6144 |
Author: Gang Fu |
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Description: matlab交叉验证cross Validation，把样本集分为训练集和测试集，防止网络出现过拟合，提高网络的泛化能力和预测精度-cross Validation for matlab，to estimate the test accuracy,training accuray and validation accuracy of a neural network
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Size: 1024 |
Author: 周杰伦 |
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Description: 一个matlab写的bp人工神经网络程序，参数优化采用交叉验证办法-Write a matlab bp artificial neural network program, parameter optimization using cross-validation method
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Size: 100352 |
Author: lifei |
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Description: matlab编写的调整svm参数的程序，其中cross是主程序，另两个是自己编写的svm核函数，如果要用matlab自带的核函数就把-t的值改成2即可。Ytrain是标记矩阵，Xtrain是特征矩阵，都由用户自己导入。可利用k倍交叉验证来选择最优的c参数。k可自行更改。-svm matlab prepared to adjust the parameters of the program, which cross the main program, and the other two are themselves prepared svm kernel function, if you use the value of the kernel function matlab own put-t can be changed to 2. Ytrain is labeled matrix, Xtrain is characteristic matrix, imported by the users themselves. K-fold cross-validation can be used to select the optimal c parameter. k can make changes.
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Size: 1728512 |
Author: wang |
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Description: ann k-fold cross validation matlab cone
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Size: 1024 |
Author: amit |
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Description: SURROGATES工具箱是一个多维函数逼近和优化方法的通用MATLAB库。当前版本包括以下功能：
实验设计：中心复合设计，全因子设计，拉丁超立方体设计，D-optimal和maxmin设计。
代理：克里金法，多项式响应面，径向基神经网络和支持向量回归。
错误和交叉验证的分析：留一法和k折交叉验证，以及经典的错误分析（确定系数，标准误差;均方根误差等;）。
基于代理的优化：高效的全局优化（EGO）算法。
其他能力：通过安全裕度进行全局敏感性分析和保守替代。(SURROGATES Toolbox is a general-purpose MATLAB library of multidimensional function approximation and optimization methods. The current version includes the following capabilities:
Design of experiments: central composite design, full factorial design, Latin hypercube design, D-optimal and maxmin designs.
Surrogates: kriging, polynomial response surface, radial basis neural network, and support vector regression.
Analysis of error and cross validation: leave-one-out and k-fold cross-validation, and classical error analysis (coefficient of determination, standard error; root mean square error; and others).
Surrogate-based optimization: efficient global optimization (EGO) algorithm.
Other capabilities: global sensitivity analysis and conservative surrogates via safety margin.)
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Size: 362496 |
Author: pluto1888 |
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