How to separate features and target (numeric values) in a tabular text datastore to import into Deep Network Design?

조회 수: 7(최근 30일)
paulo silva
paulo silva 2021년 12월 2일
편집: paulo silva 2021년 12월 8일
Hello everyone, I have the following problem: I imported a csv file with numerical data containing the features and the target into a tabular text datastore, however, to import into Deep Network Design this tabular text datastore needs to contain separate features and target. I have no idea how to do this, can someone give me a hand?
For example, my csv file has 500 rows 10 features and the target.
Thank you very much!

답변(1개)

yanqi liu
yanqi liu 2021년 12월 3일
yes,sir,may be choose the data to X and Y,such as
% 500 rows 10 features and the target.
X = Data(:, 1:10); % 10 features
Y = Data(:, end); % target
may be upload some data mat to do analysis
  댓글 수: 3
paulo silva
paulo silva 2021년 12월 4일
Hi Yanqi, thanks again for your help and proactivity. But after many tests and analysis of the structure of a tabular test datastore, I found a way that solves the issue and separates the 10 features from the target:
dsTrain = tabularTextDatastore("datasetrain.csv");
preview(dsTrain)
dsnewTrain = transform(dsTrain, @(x) [cellfun(@transpose, mat2cell(x{:,1:10},ones(1,500)),'UniformOutput',false), mat2cell(x{:,11},ones(1,500))])
preview(dsnewTrain)
dsValid = tabularTextDatastore("datasevalid.csv");
preview(dsValid)
dsnewValid = transform(dsValid, @(x) [cellfun(@transpose, mat2cell(x{:,1:10},ones(1,250)),'UniformOutput',false), mat2cell(x{:,11},ones(1,250))])
preview(dsnewValid)
dsTest = tabularTextDatastore("datasettest.csv");
preview(dsTest)
dsnewTest = transform(dsTest, @(x) [cellfun(@transpose, mat2cell(x{:,1:10},ones(1,250)),'UniformOutput',false), mat2cell(x{:,11},ones(1,250))])
preview(dsnewTest)
Again, thank you very much for your help and for those who have the same problem as me, this solution solves it simply. :)

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