R help - Nov 2003 - CLARA

I need informations about the clara routine. The on-line doc say that the
argument stand is a logical, indicating if the measurements in x are
standardized before calculating the dissimilarities. Measurements are
standardized for each variable (column), by subtracting the variable's mean
value and dividing by the variable's mean absolute deviation. If we note
STAND = TRUE, I suppose that the data will not be standardized before
clustering. On the contrary, STAND = FALSE means that the data will be
standardized before clustering.
Each sub-dataset is partitioned into k clusters using the same algorithm as
in pam. But the pam routine argument stand is a logical; if true, the
measurements in x are standardized before calculating the dissimilarities.
Measurements are standardized for each variable (column), by subtracting
the variable's mean value and dividing by the variable's mean absolute
deviation. If x is already a dissimilarity matrix, then this argument will
be ignored. If we note STAND = TRUE, I suppose that the data will be
standardized.

There is a big difference as clara and pam use nearly the same algorithm.

I need to use clara because I have a large dataset. Could help me about the
argument stand ? May I have to standardize my datas with excel before ? If
yes, what I have to write : STAND = ?? ?

Best regards,
Cordialement,

R?gis CHARIGNON
Service Optimisation
Direct Line: +33 (0)1 47 23 21 44
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>>>>> "ReCH" == optimisation1 stagiaire
<optimisation1.stagiaire at lagardere-active.com>
>>>>>     on Mon, 17 Nov 2003 11:23:41 +0100 writes:
    ReCH> I need informations about the clara routine. The
    ReCH> on-line doc say that the argument stand is a logical,
    ReCH> indicating if the measurements in x are standardized
    ReCH> before calculating the dissimilarities. Measurements
    ReCH> are standardized for each variable (column), by
    ReCH> subtracting the variable's mean value and dividing by
    ReCH> the variable's mean absolute deviation. If we note
    ReCH> STAND = TRUE, I suppose that the data will not be
    ReCH> standardized before clustering. On the contrary, STAND
    ReCH> = FALSE means that the data will be standardized
    ReCH> before clustering.  Each sub-dataset is partitioned
    ReCH> into k clusters using the same algorithm as in
    ReCH> pam. But the pam routine argument stand is a logical;
    ReCH> if true, the measurements in x are standardized before
    ReCH> calculating the dissimilarities.  Measurements are
    ReCH> standardized for each variable (column), by
    ReCH> subtracting the variable's mean value and dividing by
    ReCH> the variable's mean absolute deviation. If x is
    ReCH> already a dissimilarity matrix, then this argument
    ReCH> will be ignored. If we note STAND = TRUE, I suppose
    ReCH> that the data will be standardized.

    ReCH> There is a big difference as clara and pam use nearly
    ReCH> the same algorithm.

There is no difference between  clara() and pam() concerning the
meaning and handling of the argument `stand'.

This is very quickly seen if you look at the two functiondefinitions
which both have almost the same statement 

        x2 <-
            if (stand) 
               scale(x, scale = apply(x, 2, meanabsdev))
            else x


    ReCH> I need to use clara because I have a large
    ReCH> dataset. Could help me about the argument stand ? May
    ReCH> I have to standardize my datas with excel before ? If
    ReCH> yes, what I have to write : STAND = ?? ?

    ReCH> Best regards,
    ReCH> Cordialement,

    ReCH> R?gis CHARIGNON