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My program crashes without asking the user for sample data, how can I fix this? It worked when I tried the values of smaller datasets.
I have a Higher Education Students Performance Evaluation Dataset (https://archive.ics.uci.edu/ml/datasets/Higher+Education+Students+Performance+Evaluation+Dataset ).
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Image Analyst
2022-12-13
0 个投票
Not sure - we don't have your code or data. I'd start with carefully examining the arguments you pass to fitcknn.
8 个评论
Mustafa Furkan SAHIN
2022-12-14
编辑：Mustafa Furkan SAHIN
2022-12-14
Mustafa Furkan SAHIN
2022-12-14
now i am getting this error
Image Analyst
2022-12-14
Try getting rid of spaces and dashes in the variable names. And make sure none of the names is more than 63 characters. If that doesn't work, also make it a cell array instead of a string array.
opts.VariableNames = {'StudentAge', 'Sex', 'GraduatedHighSchoolType', .................................};
Mustafa Furkan SAHIN
2022-12-14
编辑：Mustafa Furkan SAHIN
2022-12-16
Thank you for your answer ,but unfortunately it didn't work.
The code I wrote does not read the values of this dataset.
opts = delimitedTextImportOptions("NumVariables", 8);
% Specify range and delimiter
opts.DataLines = [1, Inf];
opts.Delimiter = ",";
% Specify column names and types
opts.VariableNames = ["mcg", "gvh", "lip", "chg", "aac", "alm1", "alm2", "Class"];
opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "categorical"];
opts.ExtraColumnsRule = "ignore";
opts.EmptyLineRule = "read";
opts = setvaropts(opts, "Class", "EmptyFieldRule", "auto");
ecoliKNN = readtable("ecoliKNN.data", opts);
clear opts
modelformed = fitcknn(ecoliKNN,'Class~mcg+gvh+lip+chg+aac+alm1+alm2');
modelformed.NumNeighbors=3;
mcg=input('Enter mcg: ');
gvh=input('Enter gvh: ');
lip=input('Enter lip: ');
chg=input('Enter chg: ');
aac=input('Enter aac: ');
alm1=input('Enter alm1: ');
alm2=input('Enter alm2: ');
predict(modelformed,[mcg,gvh,lip,chg,aac,alm1,alm2])
But the code is reading this dataset (https://archive.ics.uci.edu/ml/machine-learning-databases/ecoli/)
Image Analyst
2022-12-14
Make it easy for us to help you, not hard. Attach the dataset and your m-file. Zip them up if you have to.
Mustafa Furkan SAHIN
2022-12-14
编辑：Mustafa Furkan SAHIN
2022-12-15
Image Analyst
2022-12-15
编辑：Image Analyst
2022-12-15
Do this:
t = readtable("DATA.csv");
tPredictors = t(:, 2:end);
DATA = table2array(tPredictors)
X = DATA(:, 1:31); % Input ("Predictors")
trueResponseY = DATA(:,32); % True Output (class numbers)
Then go to the Apps tab on the tool ribbon and start up the Classification Learner and start a session using data from the workspace. Tell it tPredictors is your prediction input and trueResponseY are your true response values. Then select all Bayes models, and others if you want, and tell it to train. You'll get this result:
Then go to the Export button and export the compact model into a variable. Save that variable with save() to a mat file. Then you can read in that model and give it your predictors and get the estimated class.
Mustafa Furkan SAHIN
2022-12-15
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