Man pages for linxihui/lazyML
Automatic machine learning algorithms and hyper-parameters selection
| bestMpTuneModel | methods for 'bestMpTuneModel', 'resampleMpTune' |
| combine.mpTune | combine mpTune objects |
| createModel | fit a model |
| fit | fit the best model according to 'mpTune' |
| getDefaultModel | list of list of models |
| getModelInfo | get model information |
| lazyML | Automatic machine learning algorithms selection and... |
| loopingRule | parallel looping functions |
| metric | performance metrics |
| modifyFunction | modify default arguments of a function |
| more | tune more models or do more resampling |
| more.mpTune | tune more models |
| mpTune | Model and parameter simultaneous tuning |
| mpTuneControl | Generate mpTnControl for mpTune |
| predict.coxph | predict coxph model |
| print.mpTune | print mpTune result |
| resample | Resample to evaluate performance of 'mpTune' chosen model |
| resampling | create (repeated) cross validation folds |
| SCI | A Smooth concordance loss function for mboost algorithms |
| sigest.random | Interal functions |
| summary.mpTune | summarize result from 'mpTune' |
| survival.quantiles | get survival quantiles |
