MATLAB: Resampling an unbalanced dataset

balancedatasetresample

Hi, I have a dataset which has 2 classes(churn='False.' and churn='True.'). It is unbalanced because 700 of the 5000 sample is churn='False.' Is there a way to balance that distribution? Thank you in advance.

Best Answer

Throw out all but 700 items where churn = true??? Then you'd have 700 false ones and 700 true ones. If not, then tell us in more detail what "balance" means to you.

Related Solutions

MATLAB: Detecting TRUE elements of a cell array

 y={[true; false] false; false]  [false; true]
    [true; false] false; true]  [false; false]
     true    false       false
     false    false          true}
 out1= cellfun(@(x) all(x),y)
 out2= cellfun(@(x) any(x),y)

MATLAB: Does the cellfun fails

"...however if I try to apply the same command again as..."

You have failed to take into account that inbetween running these two commands you have changed the data. So while the first cell array only contained scalar numeric (which is a bad way to store numeric data), the second time you call cellfun the cell array now also contains char vectors (lots of 'false', to be precise). Of course when you compare 'false'==1 then the output will be a vector like this:

>> 'false'==1
ans =
     0     0     0     0     0

and that is clearly not a scalar value, so your cellfun usage will fail unless you use 'uni',false and some more complex processing, or wrap the first argument function in any or something similar. Your third example give this error message

Function 'subsindex' is not defined for values of class 'cell'

because when you use the option 'UniformOutput',false then cellfun outputs a cell array, which cannot be used for indexing. So your attempt to use the output as an index will fail.

Here is a simpler approach using a numeric array (which it should be anyway):

>> m = cell2mat(a);
>> id0 = m==0;
>> id1 = m==1;
>> a(id0) = {'false'};
>> a(id1) = {'true'};
>> a
a = 
    'false'    'true'     [    2]    [    3]    [    4]    [    5]    [    6]    [    7]    [    8]    [    9]    [   10]    [   11]
    'true'     'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'
    [    2]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    3]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    4]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    5]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    6]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    7]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    8]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [    9]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [   10]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    [   11]    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'true'     'false'    'false'    'false'

Note that your row and column headers indicate that you should perhaps be using a table, or only storing the actual data (not the headers) in a simple numeric array. Then you could do this task very simply with some basic indexing:

>> c = {'false','true'};
>> b = c(1+m(2:end,2:end))
b = 
    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'false'    'false'    'false'    'false'
    'true'     'true'     'true'     'false'    'false'    'true'     'false'    'true'     'false'    'false'    'false'

Best Answer

Related Solutions

MATLAB: Detecting TRUE elements of a cell array

MATLAB: Does the cellfun fails

Related Question