Missing value for predict in Classification Learner App

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Huy Cao
Huy Cao on 17 Jan 2022
Edited: Cris LaPierre on 17 Jan 2022
Hi, I have a question. I did the Classification Step with the training step. After trainning I use test data in the App, I have added the data data into Data Test set, but there is one error it said Missing value for predict Power. Can anyone help me, cause I think my data is not missing anything
% TRAINING
trainingData=readtable("ClassificationData2.xlsx")
% The first 4 columns are the inputs.
tPredictors = trainingData(:, 1:2);
% The last column is the "answer/ground truth".
tResponse = trainingData{:, end};
testingData=readtable("ClassificationTestData2.xlsx")
tTesting=testingData(:,1:2);
ttestResponse=testingData{:,end};
T=readtable('ClassificationTestData3.xlsx')
[a,b,c]=xlsread('ClassificationTestData3');
save ClassificationTestData3 c
  2 Comments
Huy Cao
Huy Cao on 17 Jan 2022
@Image AnalystYes the fine tree, I saved the trained model with the code u send me
save('trainedModel69.mat', 'trainedModel69')
and then i loaded with load('trainedModel69.mat')
Am I right?

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Accepted Answer

Cris LaPierre
Cris LaPierre on 17 Jan 2022
Edited: Cris LaPierre on 17 Jan 2022
I was able to train using trainingData and test using testingData in R2021a without getting any errors.
Can you provide more details on what your validation settings were? What did you select for predictors and response?
I selected the table trainingData,. The variables were already correctly selected for predictors and response.. I used the default validation
For test data, I selected testingData. The variables were already correctly selected for predictors and response.
  4 Comments
Huy Cao
Huy Cao on 17 Jan 2022
Yes, this is the best answer I want to. Thank youuu

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More Answers (1)

Image Analyst
Image Analyst on 17 Jan 2022
In code you can do this:
% Load saved model.
s = load('trainedModel69.mat')
trainedModel69 = s.trainedModel69
% Read in test table with columns for power and WingSpeed.
tPredictors = readtable('ClassificationTestData3.xlsx')
% Get estimated output values based on these input values.
predictedValues = trainedModel69.predictFcn(tPredictors)

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