I have N samples of training data and M samples of test data, how i combine it together to make it MxN samples.
2 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
Balaji M. Sontakke
le 8 Mar 2020
Commenté : Balaji M. Sontakke
le 9 Mar 2020
testdata 40X1 cell
traindat 80X1 cell
train_label 80X1 double
I have N samples of training data and M samples of test data, how i combine it together to make it MxN samples. The rows, here, represent each sample and the columns the different types of features detected from a sample. also i want to add an extra column at LAST of the data (preferably): This column should represent the desired labels for the data.
2 commentaires
Ameer Hamza
le 8 Mar 2020
Modifié(e) : Ameer Hamza
le 8 Mar 2020
Can you give a simple example of what you are trying to do? For example, give us 3 training samples and 3 test samples and show us how do you want them converted to 3x3=9 samples.
Also describe what data is stored in these cell arrays.
Réponse acceptée
Ameer Hamza
le 8 Mar 2020
Following code shows how to convert the cell array from your code to the table as generated by fishertable = readtable('fisheriris.csv')
load('db3.mat');
testdata = cell2mat(reduced_testdata')';
testdata_table = array2table(testdata, ...
'VariableNames', ...
{'SepalLength', 'SepalWidth', 'PetalLength', 'PetalWidth'});
sample_labels = repmat("abcd", 40, 1); % creating random data to fill last column
% you should use your testlabels
testdata_table = addvars(testdata_table, sample_labels, ...
'NewVariableNames', 'Species');
5 commentaires
Ameer Hamza
le 8 Mar 2020
This should work in MATLAB R2016b. The code join two tables (testdata table entries above and traindata entries below). data_tables has dimension of 120x5.
load('db3.mat');
testdata = cell2mat(reduced_testdata')';
testdata_table = array2table(testdata, ...
'VariableNames', ...
{'SepalLength', 'SepalWidth', 'PetalLength', 'PetalWidth'});
sample_labels = repmat("abcd", 40, 1); % creating random data to fill last column
% you should use your testlabels
testdata_table.Species = sample_labels;
load('db4.mat');
traindata = cell2mat(reduced_traindata')';
traindata_table = array2table(traindata, ...
'VariableNames', ...
{'SepalLength', 'SepalWidth', 'PetalLength', 'PetalWidth'});
sample_labels = repmat("abcd", 80, 1); % creating random data to fill last column
% you should use your testlabels
traindata_table.Species = sample_labels;
data_tables = [testdata_table; traindata_table];
Plus de réponses (0)
Voir également
Catégories
En savoir plus sur Classification Trees 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!