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Association_analysis_code
- 支持导入外部变量数据集（例如EXCEL文件），利用MATLAB分析多个变量间的关联度。（修改代码中导入文件名称及变量个数即可）(Import the data set and use MATLAB to analyze the degree of correlation among multiple variables.(Modify the name of the imported file and the number of variables in the code.))
10 gedCFC_MATLAB
- 代码提供了一种分析多通道电生理记录中交叉频率耦合的新框架-------基于特征分解的广义交叉频率耦合框架gedcfc，共五种算法，并包括脑电信号数据集供大家验证算法。(The code provides a new framework for analyzing cross-frequency coupling in multi-channel electrophysiological recordings - gecfc based on eigen-decomposition-based g
GA-ELM
- 遗传算法优化的极限学习机模型 采用水仙花基本特征数据集 效果比单纯的ELM模型要好(The effect of using daffodils basic feature data set in the extreme learning machine model optimized by genetic algorithm is better than that of ELM model only.)
CNN
- 手写数字识别的数据集 matlab实现cnn(Data Set for Handwritten Number Recognition Realization of CNN in matlab)
bp_mnist
- matlab写的bp神经网络对mnist数据集进行学习分类(Learning and classification of MNIST data sets based on BP neural network written by MATLAB)
KPCA-故障检测
- 内附有对应的数据集，直接测试即可。利用KPCA进行降维。(With data sets, direct testing is enough.)
ELM预测
- 给出了一种极限学习机（elm)算法，并用汽油近红外光谱辛烷值数据集对ELM网络进行训练，最后用ELM对汽油辛烷值进行预测，并对预测结果进行评价。文件内含ELM工具箱，可直接在MATLAB运行。(An extreme learning machine (elm) algorithm is presented, and the ELM network is trained with the data set of gasoline near infrared spectroscopy octane
稀疏自动编码器的matlab代码
- 本资源是3层的自编码器加上稀疏正则项约束的matlab代码。隐层激活函数选sigmoid函数，输出层选线性函数，程序中以一个标准数据集sonar为例，使用该方法可以做无监督表征学习，数据压缩，多任务学习等(This resource is a 3-layer self-encoder plus matlab code for sparse regular term constraints. The hidden layer activation function selects the sigm
基于PCA的SVM分类
- 选择“BreastCancer”数据集，使用支持向量机(SVM)对其进行分类。作为对比，第一次对特征集直接进行支持向量机分类，第二次对特征集进行主成分分析法的特征提取后，再对特征提取后的特征集进行支持向量机分类。并且对比和分析了两次分类的结果。(The BreastCancer data set is selected and classified by Support Vector Machine (SVM). For comparison, the first time the featur
基于粒子群优化算法的特征选择SVM分类
- 针对“BreastCancer”数据集，作为对比，第一次对特征集直接进行SVM分类，第二次使用粒子群算法进行特征选择后再进行SVM分类。并且对比和分析了两次分类的结果。(For "BreastCancer" data set, as a comparison, the first time the feature set is directly classified by SVM, and the second time the feature set is selected
matlab
- 卷积神经网络源文件 源文件 用于图像分类 内涵数据集 与多个核函数
随机森林的matlab实现
- 随机森林的一个入门级历程，此例程可以带有稀缺数据集，让你使用训练集和测试集感受到随机森林的强大之处。随机森林的分类与回归，非常之强。秒杀神经网络，是一个人见人爱的算法。(Random forest is an entry-level process, this routine can have scarce data set, let you use training set and test set to feel the power of random forest. The classif
mocap-dense-trajectories-master
- 为了准确描述复杂时变的人体运动，卡内基梅隆大学(Carnegie Mellon University, CMU)的一个研究小组通过几个摄像头记录了各种场景下关键关节的轨迹，并建立了运动捕捉(MOCAP)数据集(To accurately describe the complex and time-varying human motion, a research group in Carnegie Mellon University (CMU) recorded the trajectories
ELM
- 极限学习机（ELM）的MATLAB完整实现程序，有完整注释并已测试通过，资源中包含了测试脚本和数据集，算法的原理和实现(The matlab implementation program of elm has a complete annotation and passed the test. The resource contains the test scr ipt and data set. The principle and implementation of the algorithm
EEG-Emotion-classification-master
- DEAP数据集下的情绪识别分类，包括特征提取和分类(Emotion recognition classification based on deap data set, including feature extraction and classification)
Model3_ANFIS
- 基于matlab的anfis模型，效果很好，但是仅适用于特征较少的数据集(Anfis model based on matlab, which works well, but only for data sets with fewer features)
NBS
- Brain Connectivity Toolbox 是一个MATLAB工具箱, 可以对结构和功能脑组织数据集进行复杂网络(图)分析.(Brain connectivity toolbox is a matlab toolbox, which can analyze complex network (graph) of structure and function brain tissue data set)
手写MNISTmatlab实现
- 资料可以直接运行，是matlab源码，实现了AI领域常见的手写字符MNIST数据集的识别，一般都是python做，matlab实现的很少，就算有也经常报错，因此这里是提供了例程以及数据集！数据集也是matlab能直接读取的MNIST格式！下载这个资料连数据集都不用单独下载了，节省时间。(The data can be run directly. It is the source code of MATLAB. It realizes the recognition of MNIST data s
KRR
- 核岭回归算法 输入数据集(需要分开存放训练集和测试集) 利用4重交叉验证法调参 最后输出分类准确率(Kernel ridge regression algorithm Input data set (training set and test set need to be stored separately) Parameter adjustment by 4-fold cross validation Final output classification accuracy)
iris
- 使用鸢尾花数据集，通过神经网络算法对鸢尾花类型进行预测(Using iris data set, the iris type was predicted by neural network algorithm.)