Azzera filtri
Azzera filtri

Classification using test and train datasets.

6 visualizzazioni (ultimi 30 giorni)
Silpa K
Silpa K il 7 Nov 2019
Commentato: Silpa K il 8 Nov 2019
For classifcation using decision tree and finding the accuracy of the classification I used the code below, but I am getting error messages. How can I find the classifcation and accuracy of the classification? Please help me.
trainData = xlsread('arrtrain.xlsx');
testData = xlsread('arrtest.xlsx');
tr = fitctree(trainData(:,2:end),trainData(:,1));
predictLabels = predict(tr,testData(:,2:end));
trueLabels = testData(:,1);
testAccuracy = sum(predictLabels == trueLabels)/length(trueLabels)*100;
The datasets are attached here.
  1 Commento
Silpa K
Silpa K il 8 Nov 2019
clc
clear
b=zeros(36,1);
ts = xlsread('ArrowHead_TRAIN.xlsx');
l=length(ts);
for i = 1:36
p=ts(i,:);
fa = movstd(p,20,1);
secarray=movstd(fa,20,1);
k=maxk(secarray,10);
mpt=find(p);
mp=p(mpt(round(numel(mpt)/2)));
G=min(abs(mp-k));
[~,ii] = min(abs(p(:) - k(:)'));
out = p(unique(ii));
for i = 1 : size(ts,1)
b = 30;
p = ts(i,:);
n = numel(p);
Z = mat2cell(p, 1, diff([0:b:n-1,n]));
end
A = [];
for ii = 1:length(Z)
if any(ismember(Z{ii},out))
if (k-mp<=G+l/2)
A{end+1} = Z{ii};
aa = ii;
end
end
end
z=Z{ii};
idx=p(1:1);
q=[idx z];
data = q;
cellReference = sprintf('A%d', i);
xlswrite('tra.xlsx', data, 1, cellReference);
end
I used the above code for getting the datasets.How can I write all the needed rows in excel.

Accedi per commentare.

Risposte (1)

Image Analyst
Image Analyst il 7 Nov 2019
You need to give it data.
Your workbooks are completely empty except for a single number in one cell way down at row 175.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by