In jakob-r/mlrHyperopt: Easy Hyperparameteroptimization with mlr and mlrMBO

On Learners

• extraTrees does "unasked parallelization" (cpu usage of 10, then )? Could be a caret, docker, java problem. But did not occur for mlr jobs.
• blackboost has overall low performance and was dropped from the experiments
• gbm often produces NaN results for higher shrinkage values and was dropped from the experiments
• Also xgbTree is very slow with caret

On Datasets

On Cartet

This script helps to crash stalled stalled containers (somehow), while others will stay running.

job.hash.running = getJobTable()[findRunning()]$job.hash
for(jh in job.hash.running) {
  did = system(sprintf('docker ps -q --filter "name=richter_bt_%s"', jh))
  system(sprintf('docker attach %s', did))
}

On mlrHyperopt

• 10.05.2017: Until experiment number 4 we probably often chose a bad resampling strategy and because of too much nois chose a bad/overfitted hyperparam config.

jakob-r/mlrHyperopt documentation built on Jan. 10, 2022, 4:32 p.m.