t lets the
> user manually specify the tuning parameters after the call to train().
>
> On Thu, Feb 9, 2012 at 7:00 PM, Yang Zhang wrote:
>> Usually when using raw glmnet I let the implementation choose the
>> lambdas. However when training via caret::train the lambda values
(I couldn't find answers to this question in the documentation)
On Fri, Feb 10, 2012 at 11:59 AM, Yang Zhang wrote:
> Sorry for not being more clear - I'm interested in accessing these
> indices from within the trainControl summaryFunction, not afterward
> (from the train obje
135] 1 2 3 4 6 7 8 9 11 12 ...
> $ Fold06: int [1:135] 1 2 3 4 5 6 7 8 9 10 ...
> $ Fold07: int [1:135] 1 2 3 4 5 7 8 9 10 11 ...
> $ Fold08: int [1:135] 2 3 4 5 6 7 8 9 10 11 ...
> $ Fold09: int [1:135] 1 2 3 4 5 6 7 8 9 10 ...
> $ Fold10: int [1:135] 1 2 4 5 6 7 8 10 11 12
Is it possible to use ROCR to plot a simple recall@p plot? I.e., a
plot where the x-axis is the position into the ranked test set, and
the y-axis is the recall, so you can see what's the recall in the top
10% of the ranked results.
I searched through the performance() manual but found nothing.
(
Actually, is there any way to get at additional information beyond the
classProbs? In particular, is there any way to find out the
associated weights, or otherwise the row indices into the original
model matrix corresponding to the tested instances?
On Thu, Feb 9, 2012 at 4:37 PM, Yang Zhang
Oops, found trainControl's classProbs right after I sent!
On Thu, Feb 9, 2012 at 4:30 PM, Yang Zhang wrote:
> I'm dealing with classification problems, and I'm trying to specify a
> custom scoring metric (recall@p, ROC, etc.) that depends on not just
> the class ou
I supply a trainControl summaryFunction, the data given
to it contains only class predictions, so the only metrics possible
are things like accuracy, kappa, etc.
Is there any way to do this that I'm looking? If not, could I put
this in as a feature request? Thanks!
--
Yang Zhang
ht
Usually when using raw glmnet I let the implementation choose the
lambdas. However when training via caret::train the lambda values are
predetermined. Is there any way to have caret defer the lambda
choices to caret::train and thus choose the optimal lambda
dynamically?
--
Yang Zhang
http
ve the Intercept from the model matrices,
since it seems to always be redundant (I usually use caret).
None of these is a big deal at all, but I'm just curious if I'm
missing something simple in how I'm doing things. Thanks.
--
Yang Zhang
http://yz.mit.edu/
_
On Wed, Feb 8, 2012 at 6:46 PM, David Winsemius wrote:
>
> On Feb 8, 2012, at 8:00 PM, Yang Zhang wrote:
>
>> I'm trying to use ROCR to create a simple cutoff vs recall plot
>> (recall@p) on the example ROCR.simple dataset:
>>
>> library(ROCR)
>
n the last line.
I'm using R 2.14.1, ROCR 1.0-4. Any ideas? Thanks in advance.
--
Yang Zhang
http://yz.mit.edu/
__
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PLEASE do read the posting guide http://www.R-project.
Are there any utilities/packages for showing various performance
metrics of a regression model on some labeled test data? Basic stuff
I can easily write like RMSE, R-squared, etc., but maybe with some
extra utilities for visualization, or reporting the distribution of
prediction confidence/varianc
caret has many useful preprocessing facilities for numeric predictors,
such as removing near-zero-variance predictors, removing correlated
predictors, removing linear combinations, centering/scaling, and
Box-Cox transformations. However, these don't work for factor data,
which is common in many le
On Wed, Jun 1, 2011 at 1:04 PM, Yang Zhang wrote:
> I can plot to png's fine when i run this directly from the top-level
> script/console:
>
> png('diamonds.png');qplot(carat,price,data=diamonds);dev.off()
>
> But for some reason it's not working when tha
I can plot to png's fine when i run this directly from the top-level
script/console:
png('diamonds.png');qplot(carat,price,data=diamonds);dev.off()
But for some reason it's not working when that's in a function:
(function(){png('diamonds.png');qplot(carat,price,data=diamonds);dev.off()})()
I su
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