Re: DM: Imputation of binary-valued features

[David L Dowe]

>From owner-datamine-l@nessie.crosslink.net Fri Aug 15 09:28:38 1997
Date: Fri, 15 Aug 1997 10:24:57 +1200
From: Murray Jorgensen <maj@waikato.ac.nz>
Subject: Re: DM: Imputation of binary-valued features

At 21:22 14/08/97 +0100, Richard Dybowski <richard@n-space.co.uk> 
wrote:
>Hi
>
>I have a dataset in which all the variables (features) are binary, 
>however,
>some of the rows of the dataset have at least one value missing. Can 
>anyone
>give me details of an E-M algorithm (for which convergence is 
>guaranteed)
>that will enable me to model the underlying probability mass 
>distribution
>thus enabling me to perform imputation? There is an established 
>method of
>doing this when the variables are real-valued (i.e. by using a 
>Gaussian
>mixture model of a multivariate pdf), but what is the approved 
>method when
>the variables are binary-valued (or a mixture of real- and 
>binary-valued
>variables)?
>
>Thanking you in advance,
>
>Richard

> I posted the following notice on Class-l in March. Unfortunately we
> still havn't got it up on our ftp site owing to other commitments, 
>but, as
> they say, real-soon-now!
> 
> To answer Richard's question, the answer for binary or 
>multi-category
> variables is known as Latent Class Analysis and the answer for when
> variables are both continuous and categorical is our MULTIMIX.
> 
> Our earlier announcement follows:


Hi, Murray.

As well as Murray's MULTIMIX,
you are welcome to also try

1)  my Snob program with Chris Wallace, founder of Minimum Message 
Length
    (MML), at http://www.cs.monash.edu.au/~dld/Snob.html

2)  As well as MULTIMIX and Snob, any other mixture modellers at
    http://www.cs.monash.edu.au/~dld/mixture.modelling.page.html  ,
    although Snob and MUTLIMIX are two of few (and possibly the only 
two) that
    deal with both multi-state variables and missing data.



Best wishes.     - David.

(Dr.) David Dowe, Dept of Computer Science, Monash University, 
Clayton,
Victoria 3168, Australia  dld@cs.monash.edu.au     Fax:+61 3 9905-5146
http://www.cs.monash.edu.au/~dld/
http://www.cs.monash.edu.au/~dld/Snob.html
http://www.cs.monash.edu.au/~dld/mixture.modelling.page.html