搜索资源列表
SENSEaliasingmatrix
- 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 indicat
SimpleSENSEreconstruction
- 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 im
AI_Blood
- 本次大作业利用K‐近邻（K‐Nearest Neighbor）算法，为给定的训练数据集构造了分类器， 并在测试数据集上进行分类预测，同时计算了Accuracy、Precision、Recall和F‐measure，利用 10‐fold的实验方法进行交叉验证。-The big job to use K-neighbor (K-Nearest Neighbor) algorithm, for a given set of train
sift-latest_win
- 修改过的lowe在04年的算法及程序。 可运行。并且卷积过程是卷积k倍尺度的高效sift.-Modified lowe algorithm in 2004 and procedures. Can run. And k-fold convolution convolution process is efficient scale sift.
svm4
- -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：tan
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
FeatureSelection_MachineLearning
- 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 hyperpareme
cross-validation
- 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
bpcross
- 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
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 par
KNN
- Implement the K nearest neighbor algorithm by your own instead of using available software. 2. Use K-fold cross validation to generate training and testing datasets. You should try different K values (3~8) to see how t
create_kfolds_balanced_train_test
- Divide/Create data into K-Folds training and testing data which are balanced basing on the labels. It is for k-fold cross validation.
crossvalidation_svm
- 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 pr
ANN-k-fold-cross-validation
- ann k-fold cross validation matlab cone
svm-regression-k-fold-cross-validation
- SVM with K-fold cross validation
lvq
- code for lvq and split the data to be train and test by k-fold cross validation with k=5
K-fold-crossvalidate
- 神经网络的K折交叉验证用于模型选择和测试数据验证-crossvalidate of ANN
k-fold_cross-validation_binary_libsvm
- k-fold svm which downloaded before.
K-fold-Cross-Validation-master
- 进行K折交叉验证，将数据分为K份，将1份作为TEST，剩下K-1份作为TRAINING，对TEST进行测试(K folding cross validation)
SRGTSToolbox
- 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