this is attempt at iregnet pred #2
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hi @andruuhurst please commit and push your changes so I can code review. |
iregnet.predictions.R
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| keep.inputs <- apply(is.finite(data.list$inputs), 2, all) | ||
| data.list$inputs <- data.list$inputs[, keep.inputs, drop=FALSE] | ||
| #order.dt <- fread(testFold.csv) | ||
| testFold.dt <- fread(testFold.csv) |
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iregnet.predictions.R
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| for( model.type in c( "gaussian", "logistic", "extreme_value")){ | ||
| for( scale.type in scale.i.list){ | ||
| fit.list[length(fit.list) + 1] <- cv.iregnet(X.train, Y.train , family = model.type, |
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Hey @tdhock
the for loops iterate through until it gets to the extreme_value. then I get this error
Error in stopifnot_error(paste("family must be one of", paste(names(pfun.list), : family must be one of gaussian, logistic, exponential
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I tried using iregnet( ...., extreme_value,..) instead and it returned this error
Error in dimnames(x) <- dn :
length of 'dimnames' [1] not equal to array extent
any thoughts?
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first of all you should use cv.iregnet (which automatically performs selection of regularization/penalty parameter) and not iregnet (which does not perform selection).
for a quick fix I would suggest using only logistic and gaussian (remove extreme value).
also please post a minimal reproducible example as an issue on https://github.com/anujkhare/iregnet/issues . Make sure to include what version of the software you are using, via the packageDescription command, this is what it looks like on my system,
> packageDescription("iregnet")
Package: iregnet
Type: Package
Title: Regularized interval regression
Version: 0.1.0.9000
Author: Anuj Khare <khareanuj18@gmail.com>, Toby D Hocking
<toby.hocking@r-project.org>, Jelle Goeman, Aditya Samantaray
<aditya.samantaray1@gmail.com>
Maintainer: Anuj Khare <khareanuj18@gmail.com>, Aditya Samantaray
<aditya.samantaray1@gmail.com>
Description: Interval regression with four types of censoring and
elastic net regularization.
License: GPL-3
LazyData: TRUE
Suggests: ElemStatLearn, glmnet, testthat, knitr, rmarkdown
LinkingTo: Rcpp
Depends: R (>= 2.10)
Imports: ggplot2, utils, methods, stats, survival, foreach, doParallel,
data.table, Matrix, namedCapture, penaltyLearning
RoxygenNote: 6.1.1
Remotes: tdhock/penaltyLearning
VignetteBuilder: knitr
RemoteType: github
RemoteHost: api.github.com
RemoteRepo: iregnet
RemoteUsername: anujkhare
RemoteRef: 4d77f047c3a00a5524e1cbe140226417e3aedd92
RemoteSha: 4d77f047c3a00a5524e1cbe140226417e3aedd92
GithubRepo: iregnet
GithubUsername: anujkhare
GithubRef: 4d77f047c3a00a5524e1cbe140226417e3aedd92
GithubSHA1: 4d77f047c3a00a5524e1cbe140226417e3aedd92
NeedsCompilation: yes
Packaged: 2019-07-19 18:40:17 UTC; th798
Built: R 3.6.1; x86_64-w64-mingw32; 2019-07-19 18:40:18 UTC; windows
-- File: C:/Users/th798/R/win-library/3.6/iregnet/Meta/package.rds
>
| @@ -0,0 +1,131 @@ | |||
| sequenceID,V1 | |||
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this is a good start but please use a more informative column name instead of V1. for example typically I use pred.log.penalty or pred.log.lambda
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When trying to add the remaining pred files I was receiving this error
Error in dimnames(x) <- dn :
length of 'dimnames' [1] not equal to array extent
In addition: Warning message:
In fit_cpp(x.train, y, family, alpha, lambda_path = lambda, num_lambda = num_lambda, :
Ran out of iterations and failed to converge.
What's weird is that I would get this error inconsistently. I could retry it on the same data set and get a result and other times I won't. I have been working on it but could not figure out why it is happening
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which data sets do you get that error on? I would imagine it depends on the random seed that you use, see any result figures yet? |
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@tdhock yes, I got a rough figure of one we discussed |
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that's a good start, but it would be better to use a dotplot ( |
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@tdhock absolutely, I'll get right on that. |
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