MATLAB深度学习代码
时间: 2023-05-28 09:08:09 浏览: 393
作为一个AI语言,MATLAB在深度学习领域也有着广泛的应用。下面是一些常用的MATLAB深度学习代码:
1. 数据读取:
```
imds = imageDatastore('path_to_data_folder','IncludeSubfolders',true,'LabelSource','foldernames');
```
2. 卷积神经网络(CNN):
```
layers = [imageInputLayer([28 28 1]);
convolution2dLayer(5,20);
reluLayer();
maxPooling2dLayer(2,'Stride',2);
fullyConnectedLayer(10);
softmaxLayer();
classificationLayer()];
```
3. 递归神经网络(RNN):
```
layers = [sequenceInputLayer(inputSize);
lstmLayer(hiddenSize,'OutputMode','last');
fullyConnectedLayer(numClasses);
softmaxLayer();
classificationLayer()];
```
4. 支持向量机(SVM):
```
SVMModel = fitcsvm(features,labels,'KernelFunction','rbf','BoxConstraint',1);
```
5. K均值聚类:
```
[idx,C] = kmeans(features,numClusters);
```
6. 数据增强:
```
imageAugmenter = imageDataAugmenter('RandXReflection',true,'RandRotation',[-10 10],'RandScale',[0.9 1.1]);
augimds = augmentedImageDatastore(outputSize,imds,'DataAugmentation',imageAugmenter);
```
7. 损失函数:
```
lgraph = layerGraph(layers);
classWeights = [1 1 1 1 1 1 1 1 1 1];
classWeights = 1./sqrt(classWeights);
classWeights = classWeights/sum(classWeights);
pixelClassificationLayer = pixelClassificationLayer('Name','labels','Classes',categorical(0:9),'ClassWeights',classWeights);
lgraph = replaceLayer(lgraph,'classification',pixelClassificationLayer);
lgraph = connectLayers(lgraph,'softmax','labels');
```
这些代码是MATLAB深度学习中的一些示例,可以帮助您更好地理解MATLAB在深度学习中的应用。
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