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List:       wekalist
Subject:    Re: [Wekalist] Latent semantic analysis in weka
From:       Mark Hall <mhall () pentaho ! com>
Date:       2013-01-30 8:23:43
Message-ID: CD2F3F18.599D%mhall () pentaho ! com
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On 25/01/13 8:20 AM, "mksaad" <motaz.saad@gmail.com> wrote:

>Hello,=20
>
>I have read some articles about "Latent semantic analysis". the key point
>is
>that LSA tries to find relations between terms by producing a set of
>concepts related to the documents and terms.
>
>But in weka, it is used for dimensions reduction (feature selection). I
>would appreciate if you point me to a reference that describe how LSA is
>used in dimensions reduction in weka.

LSA is similar to PCA in that it transforms the attribute space by
creating new features that are linear combinations of the original ones.
Dimensionality is reduced by using fewer transformed attributes than the
full set.

Cheers,
Mark.




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