Convolution Neural network for regression problems
27 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
Hi everyone
I want to use CNN for my problem. The existing examples in the MATLAB (Here) provided for images as 4-D arrays but my problem is as follows:
Inputs = N (78000,24)
Output = Y(78000,1)
How can I use the mentioned examples for my problem?
Thanks in advanced.
1 commentaire
Réponse acceptée
yanqi liu
le 11 Jan 2022
yes,sir,may be use rand data to simulate your application,then you can replace data,such as
clc; clear all; close all;
% Inputs = N (78000,24);
% Output = Y(78000,1);
Inputs = randn(78000,24);
Output = rand(78000,1);
% get input data matrix
XTrain=(reshape(Inputs', [24,1,1,78000]));
YTrain=Output;
layers = [imageInputLayer([24 1 1])
convolution2dLayer([15 1],3,'Stride',1)
batchNormalizationLayer
reluLayer
maxPooling2dLayer(2,'Stride',2,'Padding',[0 0 0 1])
dropoutLayer
fullyConnectedLayer(1)
regressionLayer];
miniBatchSize = 128;
options = trainingOptions('sgdm', ...
'MiniBatchSize',miniBatchSize, ...
'MaxEpochs',30, ...
'InitialLearnRate',1e-3, ...
'LearnRateSchedule','piecewise', ...
'LearnRateDropFactor',0.1, ...
'LearnRateDropPeriod',20, ...
'Shuffle','every-epoch', ...
'Plots','training-progress', ...
'Verbose',false);
net = trainNetwork(XTrain,YTrain,layers,options);
3 commentaires
Plus de réponses (1)
Voir également
Catégories
En savoir plus sur Sequence and Numeric Feature Data Workflows dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!