Hmmm.. I'll try that.
I recall reading somewhere that the "group" variable had to be indicated
in a special way.
-N
On 8/4/09 3:49 PM, David Winsemius wrote:
>
> On Aug 4, 2009, at 6:45 PM, Noah Silverman wrote:
>
>> I guess I didn't explain it well enough.
>>
>> I have a number of training examples. They have 4 fields.
>> label, v1, v2, group
>>
>> The label is binary ("yes", "no")
>>
>> My understanding (Quite possible wrong.) was that there was a way to
>> train the LR to estimate probabilities "per group"
>>
>> In pseudo-code it would be:
>> lrm( label ~ v1 + v2, group_by(group)
>>
>
> Why not :
>
> lrm( label ~ v1 + v2 + group)
>
> ?
>
>>
>> On 8/4/09 3:41 PM, David Winsemius wrote:
>>>
>>> On Aug 4, 2009, at 6:38 PM, Noah Silverman wrote:
>>>
>>>> Thanks David,
>>>>
>>>> But HOW do I indicate the "grouping" variable in the formula?
>>>
>>> Hard to tell. You have told us absolutely nothing about the problem.
>>> Discrete variables cause no problems in formulas. Perhaps one of :
>>>
>>> ?factor
>>> ?cut
>>> ?quantile
>>>
>>>>
>>>> Thanks!
>>>>
>>>> -N
>>>>
>>>> On 8/4/09 3:37 PM, David Winsemius wrote:
>>>>>
>>>>> On Aug 4, 2009, at 6:33 PM, Noah Silverman wrote:
>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> Trying to setup a logistic regression model. (Something new to
>>>>>> me. I
>>>>>> usually use SVM.)
>>>>>>
>>>>>> The person explaining the concept explained to me that I can
>>>>>> include a
>>>>>> "group" variable so that the probabilities predicted by the model
>>>>>> will
>>>>>> be "per group"
>>>>>>
>>>>>> Does this make sense to anyone?
>>>>>
>>>>> Yes.
>>>>>
>>>>>> If so, how would I implement this?
>>>>>> Using the glm or lrm function?
>>>>>
>>>>> Yes.
>
> David Winsemius, MD
> Heritage Laboratories
> West Hartford, CT
>
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