What was the question and answer here?
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From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
On Behalf Of pdb
Sent: Sunday, July 11, 2010 5:23 AM
To: r-help@r-project.org
Subject: Re: [R] eliminating constant variables
Importance: Low
Awsome!
It
Awsome!
It made sense once I realised SD=standard deviation !
pdb
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On Sat, Jul 10, 2010 at 6:28 PM, pdb wrote:
>
> Hi all,
>
> I have a large data set and want to immediately build a 'blind' model
> without first examining the data. Now it appears in the data there are a lot
> of fields that are constant or all missing values - which prevents the model
> from bei
Yep - that is what I want.
Cheers Jim you Legend.
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R-help@r-project.org ma
Is this what you want:
> test <- data.frame(a=runif(10), b=rep(NA, 10), c=rep(3,10), d=runif(10))
> test
a b c d
1 0.3390729 NA 3 0.4346595
2 0.8394404 NA 3 0.7125147
3 0.3466835 NA 3 0.344
4 0.3337749 NA 3 0.3253522
5 0.4763512 NA 3 0.7570871
6 0.8921983 NA 3 0.20269
Hi Jim,
Thanks for your response, although I was probably not clear about exactly
what I want to achieve, please let me see if I can explain a little
better...
There are certain (unknown) columns in my data that contain either NULL in
every row, or the same value in every row (eg '1'). These co
You can remove NAs with:
train <- subset(train, !is.na(TargetVariable))
I am not sure what you mean by constant values. You could use 'table'
to determine which values appear the most and then remove them:
x <- table(train$TargetVariable)
train <- subset(train, !(TargetVariable %in% names(x)[x
Hi all,
I have a large data set and want to immediately build a 'blind' model
without first examining the data. Now it appears in the data there are a lot
of fields that are constant or all missing values - which prevents the model
from being built.
Can someone point me the right direction as to
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