My dataset consists of 322 samples in four categories, with the last column being labeled，Please help me take a look at my code and why the accuracy is very low？

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wentong
wentong 2023-6-15
评论： Ranjeet 2023-6-30
Ran in:
%% 读取数据
dataset=readmatrix('borsmote_data.xlsx');
sz = size(dataset);
dataset = dataset(randperm(sz(1)),:);
traindata=dataset(:,1:7);
trainlabel=categorical(dataset(:,8));
classes = unique(trainlabel)
classes = 4×1 categorical array
1 2 3 4
numClasses = numel(unique(trainlabel))
numClasses = 4
%% 划分训练集和数据集
PD = 0.8 ;
Ptrain = []; Ttrain = [];
Ptest = []; Ttest = [];
for i = 1 : length(classes)
indi = find(trainlabel==classes(i));
indi = indi(randperm(length(indi)));
indj = round(length(indi)*PD);
Ptrain = [Ptrain; traindata(indi(1:indj),:)]; Ttrain = [Ttrain; trainlabel(indi(1:indj),:)];
Ptest = [Ptest; traindata(indi(1+indj:end),:)]; Ttest = [Ttest; trainlabel(indi(1+indj:end),:)];
end
Ptrain=(reshape(Ptrain', [7,1,1,size(Ptrain,1)]));
Ptest=(reshape(Ptest', [7,1,1,size(Ptest,1)]));
layers = [imageInputLayer([7 1 1])%输入层
convolution2dLayer([3 1],10,'Stride',1)
batchNormalizationLayer%批归一化
reluLayer%激活
maxPooling2dLayer(2,'Stride',2,'Padding',[0 0 0 1])%池化层
dropoutLayer
fullyConnectedLayer(numClasses)%全连接层输出大小
softmaxLayer
classificationLayer];
options = trainingOptions('adam', ...
'MaxEpochs',5000, ...
'InitialLearnRate',1e-4, ...
'Shuffle','every-epoch', ...
'Plots','training-progress', ...
'Verbose',false, ...
'ValidationData',{Ptest,Ttest},...
'ExecutionEnvironment', 'cpu', ...
'ValidationPatience',Inf);
net = trainNetwork(Ptrain,Ttrain,layers,options);
Error using trainNetwork
This functionality is not available on remote platforms.

Caused by:
Error using matlab.internal.lang.capability.Capability.require
This functionality is not available on remote platforms.

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采纳的回答

Ranjeet
Ranjeet 2023-6-26
Hi Wentong,
As per the dataset/information provided, there are only 322 samples collectively for all the classes.
The dataset size seems to be quite small to get a good accuracy from a NN. I see that the number of epochs is set to 5000, but the primary reason for low accuracy seems the small dataset size.
It is suggested to get more data samples, there is no upper limit but training with 5000 data samples should show better accuracy.
Also, try maintaining a balanced dataset (equivalent size of data of each class).
  2 个评论
wentong
wentong 2023-6-30
Hi Ranjeet
It's a great pleasure to communicate with you
Is there no optimization algorithm that can improve accuracy？such as PSO，But I don't quite understand how to add the above code
Ranjeet
Ranjeet 2023-6-30
Hi @wentong,
As per the code and dataset provided, the suggested approach would be to add more samples to the dataset (as suggested in the answer) to improve accuracy. PSO algorithm would not be useful in this context to increase accuracy.

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