I have a set of timestamp data that I have in a text file that I would like
to import into R for analysis.
The timestamps are formated as follows:

DT_1,DT_2
[2006/08/10 21:12:14 ],[2006/08/10 21:54:00 ]
[2006/08/10 20:42:00 ],[2006/08/10 22:48:00 ]
[2006/08/10 20:58:00 ],[2006/08/10 21:39:00 ]
[2006/08/04 12:15:24 ],[2006/08/04 12:20:00 ]
[2006/08/04 12:02:00 ],[2006/08/04 14:20:00 ]

I can get them into R but I cannot figure out how to convert them into
something R will recognize as a date/time. I have tried using "as.Date",
strptime, and chron. Any help would be appreciated?

best,

Spencer



On 1/4/07, Darin A. England <england@cs.umn.edu> wrote:
>
>
> Does anyone know a reason why, in principle, a call to randomForest
> cannot accept a data frame with missing predictor values? If each
> individual tree is built using CART, then it seems like this
> should be possible. (I understand that one may impute missing values
> using rfImpute or some other method, but I would like to avoid doing
> that.)
>
> If this functionality were available, then when the trees are being
> constructed and when subsequent data are put through the forest, one
> would also specify an argument for the use of surrogate rules, just
> like in rpart.
>
> I realize this question is very specific to randomForest, as opposed
> to R in general, but any comments are appreciated. I suppose I am
> looking for someone to say "It's not appropriate, and here's why
> ..." or "Good idea. Please implement and post your code."
>
> Thanks,
>
> Darin England, Senior Scientist
> Ingenix
>
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> PLEASE do read the posting guide
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>

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