Hi Jannis,

  Thank you for answering my question. I saw the option called na.omit when
i used nnet() and tried to classify Iris data with that. I wanted to know if
there is a similar option available in kmeans which can omit or in some way
consider the null/NA values and cluster the observations.Currently, kmeans
throws an error for the dataset with NULL/NA values.

>From your answer, i could understand that, the option of handling NULL/NA is
not available with kmeans. Please correct me if am wrong.

Thanks again :)

On Wed, Dec 15, 2010 at 6:50 PM, Jannis <bt_jannis@yahoo.de> wrote:

> I do not really understand your question. You can use use kmeans but
> without the observations that include the NA values (e.g. by deleting whole
> rows in your observation matrix). If you want to keep the information in the
> valid observations of those rows, I fear you need to look for a clustering
> algorithm that can handle missing values. I doubt that there is a kmeans
> version that can. Think about inserting means of all other observations into
> the gaps, though this introduces bias as well.
>
>
> Jannis
>
> Raji schrieb:
>
>  Hi,
>>
>>  I am using k means algorithm for clustering.My data contains a few
>> null/NA
>> values.kmeans doesnt cluster with those values.Are there any option like
>> na.omit which can avoid these null values and cluster the remaining
>> values?
>>
>> Thanks,
>> Raji
>>
>>
>
>

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