Dividing the dataset into training and validation sets

[Johnny Amora]

The training set and validation set will be created from a database
consisting of 100 variables and 4000 cases.  One variable called "group" has 5
categories: A, B, C, D and E.  The training set should be 70% random sample from
the entire database.  However, the cases for the training set should be
selected proportionately according to the proportion of A, B, C, D and E in the
entire data set.  Assuming that the proportions of A,B,C D and E are .5, .10, 20, .30, and .35, respectively, can this be done through syntax?

  
Thank you.
Johnny


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[Spousta Jan]

Hi John,

Try this:


compute random = uniform(100).
SORT CASES BY group(A) random(A).
compute sample = 1.
if any(MOD($casenum,10), 2, 5, 8) sample = 0.
exe.
val lab sample 0 "validation" 1 "training".

CROSSTABS
  /TABLES=group BY sample
  /FORMAT=AVALUE TABLES
  /CELLS=COUNT ROW
  /COUNT ROUND CELL.

Best regards,

Jan

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Johnny Amora
Sent: Tuesday, October 21, 2008 9:10 AM
To: [hidden email]
Subject: Dividing the dataset into training and validation sets

The training set and validation set will be created from a database consisting of 100 variables and 4000 cases.  One variable called "group" has 5
categories: A, B, C, D and E.  The training set should be 70% random sample from the entire database.  However, the cases for the training set should be selected proportionately according to the proportion of A, B, C, D and E in the entire data set.  Assuming that the proportions of A,B,C D and E are .5, .10, 20, .30, and .35, respectively, can this be done through syntax?


Thank you.
Johnny


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Now you can @ymail.com and @rocketmail.com.
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