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Date:         Wed, 15 Dec 2004 09:45:26 -0600
Reply-To:     Anthony Babinec <>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Anthony Babinec <>
Subject:      Re: Discriminant Analysis
Comments: To: jatender mohal <>
In-Reply-To:  <000001c4e290$574675e0$32d5a78f@LoveBird>
Content-Type: text/plain; charset="us-ascii"

Jatender, Randomly assign the data to Training(1) or Validation(0) data sets. There are different ways to do this using COMPUTE, for example. Then, on the main DISCRIMINANT dialog box, move this created variable to the Selection Variable entry, and designate 1 as the Value. DISCRIMINANT will calculate its coefficients based on the training sample, and will classify both the selected and unselected cases. Be sure to click the Classify.. button on the main menu and ask for Summary table.

Having said that, the sample size of 30 is rather small, and your answer can be contingent on the allocation of cases to Training and Validation sets. With only 10 cases in the Validation set, you cannot get a precise estimate of error.

Anthony Babinec

-----Original Message----- From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of jatender mohal Sent: Wednesday, December 15, 2004 4:25 AM To: SPSSX-L@LISTSERV.UGA.EDU Subject: Discriminant Analysis

Hi list. Many thanks in advance!

I have run a discriminant analysis based on features(x1, x2 .) for two classes of an output variable on 30 patterns (data points). Using pull down menu, flexibility is very limited. I have to use my all data points for discriminant function. Then leave-one out cross validation method is used on all same 30 patterns to gauge the generalization ability of the developed discriminate function into the classes. Can I work on this problem in SPSS this way? Design a model on 20 patterns, measure the performance of function to classify data items in to classes After that, use 10 withheld patterns for generalisation of the developed model. Any suggestion!

Jatender Mohal

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