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https://github.com/cran/automl
28 March 2020, 16:12:19 UTC
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Tip revision: ab2d7c8d13ae85f6be55b525f76ffcc2f94052ef authored by Alex Boulangé on 16 January 2020, 10:40:09 UTC
version 1.3.2
Tip revision: ab2d7c8
NEWS
automl 1.3.2
============================================
* one step forward, one step back!
  MAPE cost function is back and validated
  RMSE cost function removed (derivative
  challenge + no added value vs MSE imo)
* bug fix: 'chkgradevery' is now available

automl 1.3.1
============================================
* direct ‘overfitting’  &  ‘regularization’
  modes for auto_runtype
* batch normalization set to 0 by default
  (not good for regression targets)
* bug fix: now exits if no gain when no cros-
  s validation sample
* bug fix: testgainunder now kept as is
* MAPE cost function removed (probably an er-
  ror to be fixed in derivative: todo list)

automl 1.3.0
============================================
* rmse & mape cost function added for regres-
  sion

automl 1.2.9
============================================
* documentation update (typo correction and
  more detailed explanations concerning
  modexec and autopar)
  thanks to Alexey

automl 1.2.8
============================================
* time limit for sub modelizations in automl_
  train function, to avoid waiting too long
  for a specific particle to finish its mode-
  lization

automl 1.2.7
============================================
* lightening models produced by removing
  unnecessary data (Z, A layers, etc...)

automl 1.2.6
============================================
* just a proper Authors@R field 4 CRAN :-)

automl 1.2.5
============================================
* automl_train bug fix when particle produces
  no exploitable model (continued work)

automl 1.2.4
============================================
* automl_train bug fix when particle produces
  no exploitable model

automl 1.2.3
============================================
* dropout bug fix (now random at each mini
  batch and reproductible)
* bug fix: continue training on auto trained model
  with manual function

automl 1.2.2
============================================
* pkgdown site with vignettes (Rmd file added)

automl 1.2.1
============================================
* pkgdown site (nb: Rnw vignettes are not included)

automl 1.2.0
============================================
* New param 'mdlref' for automl_train_manual:
  to start training from saved model (shape,
  weights...) for fine tuning
* New param 'mdlref' for automl_train:
  to start training with loaded hpar and autopar
  (not the model)
* New 'auto_runtype' autopar for automl_train
  to run automatically the 2 steps below;
  1: overfitting, goal: performance
  2: regularization, goal: generalization
* dropout bug fix
* lambda bug fix

automl 1.1.0
============================================
* same train/test sampling for each particle with automl_train
* stick to a format in variables naming

automl 1.0.9
============================================
* testcvsize = 0 bug fix

automl 1.0.8
============================================
* New automatic hyperparameters adjustments below:
  'auto_psovelocitymaxratio' autopar PSO velocity max ratio
  'auto_layer' autopar layer shape (layers number, nodes
  number per layer, activation types and dropout ratios)
* 'auto_lambda' bug fix

automl 1.0.7
============================================
* vignette completion

automl 1.0.6
============================================
* vignette howto_automl: why, how and basic howto
* 'auto_lambda' autopar regularization hyperparameter
* seed bug fix for reproductibility
* display enhancement in NN structure display

automl 1.0.5
============================================
* first public release on CRAN
* There's so much to do; transfert learning, CNN, RNN ...
  feel free to join

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