SebGGruber
commented
4 years ago More detailed explanation of the error:
I installed the newest github version of mlr3, mlr3tuning, mlr3pipelines, paradox, checkmates and autoxgboost and executed the following script:
library(autoxgboost)
library(mlr3tuning)
library(mlr3)
library(paradox)
library(checkmate)
data="data/abalone"
task = readRDS(file.path(data, "task.rds"))
axgb_settings = autoxgboost_space(task, tune.threshold = FALSE)
rsmp_inner = axgb_settings$resampling
learner = axgb_settings$learner
ps = axgb_settings$searchspace
ti = TuningInstance$new(task = task, learner = learner, resampling = rsmp_inner, param_set = ps, measures = msr("classif.ce"), terminator = term("evals", n_evals = 1))
tuner = tnr("random_search")
tuner$tune(ti)which gives the following console output in a newly started R session:
> library(autoxgboost)
Loading required package: paradox
Loading required package: mlr3
Loading required package: mlr3pipelines
Loading required package: mlr3learners
> library(mlr3tuning)
Attaching package: ‘mlr3tuning’
The following object is masked from ‘package:stats’:
terms
> library(mlr3)
> library(paradox)
> library(checkmate)
> data="data/abalone"
> task = readRDS(file.path(data, "task.rds"))
> axgb_settings = autoxgboost_space(task, tune.threshold = FALSE)
rsmp_inner = axgb_settings$resampling
> rsmp_inner = axgb_settings$resampling
> learner = axgb_settings$learner
> ps = axgb_settings$searchspace
> ti = TuningInstance$new(task = task, learner = learner, resampling = rsmp_inner, param_set = ps, measures = msr("classif.ce"), te
rminator = term("evals", n_evals = 1))
> tuner = tnr("random_search")
> tuner$tune(ti)
INFO [13:22:06.027] Starting to tune 8 parameters with '<TunerRandomSearch>' and '<TerminatorEvals>'
INFO [13:22:06.056] Terminator settings: n_evals=1
INFO [13:22:06.108] Evaluating 1 configurations
INFO [13:22:06.120] xgboost.eta xgboost.gamma xgboost.max_depth xgboost.colsample_bytree xgboost.colsample_bylevel xgboost.lambda
xgboost.alpha
INFO [13:22:06.120] 0.08478911 5.979535 5 0.872689 0.6943021 -8.741068
-3.629845
INFO [13:22:06.120] xgboost.subsample
INFO [13:22:06.120] 0.8994385
Error in (function (xs) :
Assertion on 'xs' failed: The parameter 'lambda' can only be set if the following condition is met 'booster = gblinear'. Instead
the parameter value for 'booster' is not set at all. Try setting 'booster' to a value that satisfies the condition.
>R session info:
> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 19.10
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.3.7.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=de_DE.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=de_DE.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=de_DE.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] checkmate_2.0.0 mlr3tuning_0.1.2-9000 autoxgboost_0.0.0.9000 mlr3learners_0.1.6 mlr3pipelines_0.1.2.9000
[6] mlr3_0.1.7-9000 paradox_0.1.0-9000 nvimcom_0.9-83
loaded via a namespace (and not attached):
[1] lgr_0.3.3 mlr3misc_0.1.8-9000 digest_0.6.25 crayon_1.3.4 withr_2.1.2 R6_2.4.1
[7] mlr3measures_0.1.2 backports_1.1.5 uuid_0.1-4 data.table_1.12.8 tools_3.6.1 compiler_3.6.1
mb706
use task from mattermost file