Thank you for pointing me to ?dissimilarity.object. I now see that N = Nominal
(factor) and I = Interval scaled (numeric).
Regards.
On Sun, Feb 24, 2013 at 2:36 PM, Peter Ehlers <ehl...@ucalgary.ca> wrote:
> On 2013-02-24 07:57, Joanna Papakonstantinou wrote:
>
>> I am using the iris dataset that contains mixed variables (some columns
>>> are numeric and some categorical).
>>>
>>> iris
>>>>
>>> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
>>> 1 5.1 3.5 1.4 0.2 setosa
>>> 2 4.9 3.0 1.4 0.2 setosa
>>> 3 4.7 3.2 1.3 0.2 setosa
>>> 4 4.6 3.1 1.5 0.2 setosa
>>> .
>>> .
>>> .
>>>
>>
>> I am trying to use the Gower metric so that I may specify that some
>>> columns contain categorical data.
>>>
>>>> iris.clust<-daisy(iris, metric = "gower", stand = FALSE, type =
>>>> list(factor="Species"))
>>>>
>>> But it is saying that the types= I, I, I, I, N
>> so obviously it is not reading the variable types correctly.
>>
>
> I don't know why you say that. Look at ?dissimilarity.object to see
> what 'I' and 'N' mean.
>
> If you read the help page for ?daisy carefully, you'll see that your
> command is equivalent to
>
> iris.clust(iris)
>
> i.e. you need not specify the metric etc.
> BTW, your specification of 'type' indicates that you may have
> looked at the help page a bit too hastily.
>
>
>
>> Could someone please tell me how to specify the variable types correctly?
>>
>> Thank you.
>> Joanna
>>
>
> Peter Ehlers
>
>
--
******************************************************************
*Joanna Papakonstantinou, Ph.D.*
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