How can I do a 80-20 split on datasets to obtain training and test datasets?

I tried [training, test] = partition (faceDatabase, [0.8, 0.2]); but it gives me error. Can anyone help? Are there ways to do this manually? I can't find a function for this!

[Akira Agata]

How about using cvpartition ?

[Chidiebere Ike]

OK. Thanks for your response. I will give it a try. But can this be achieved via a for loop??

Answer 1

[KSSV]

Let P and T be your input and target sets.

PD = 0.80 ;  % percentage 80%
Ptrain = P(1:round(PD*length(T)),:) ; Ttrain = T(1:round(PD*length(T))) ;
Ptest = P(round(PD*length(T)):end,:) ;Ttest = T(round(PD*length(T)):end) ;

[Chidiebere Ike]

I tried the code, it says "undefined function or variable T"... I will appreciate if you describe the letter P, T and length ... How do I resolve this. ?

[Prasobhkumar P. P.]

P and T corresponds to each labels (or categories)

Answer 2

[Akira Agata]

If you want to randomly select 80% of your data as training dataset, please try following:

PD = 0.80 ;  % percentage 80%

% Let P be your N-by-M input dataset

% Solution-1 (need Statistics & ML Toolbox)
cv = cvpartition(size(P,1),'HoldOut',PD);
Ptrain = P(cv.training,:);
Ptest = P(cv.test,:);

Another possible solution:

% Solution-2 (using basic MATLAB function)
N = size(P,1);
idx = randperm(N);
Ptrain = P(idx(1:round(N*PD)),:);
Ptest = P(idx(round(N*PD)+1:end),:);

[Chidiebere Ike]

Solution 1 gives an error message.. Error in cvpartition CV.Impl = internal.stats.cvpartitionInMemoryImpl(varargin{:});

Answer 3

[Munshida P]

This will help you.

[training,test] = partition(faceDatabase,[0.8 0.2]);