brulee 0.6.0

• Transition from the magrittr pipe to the base R pipe.

• To try to help avoiding numeric overflow in the loss functions:

  • Tensors are stored as a 64-bit float instead of 32-bit.

  • Starting values were transitioned to using Gaussian distribution (instead of uniform) with a smaller standard deviation.

  • The results always contain the initial results to use as a fallback if there is overflow during the first epoch.

  • brulee_mlp() has two additional parameters, grad_value_clip and grad_value_clip, that prevent issues.

  • The warning was changed to “Early stopping occurred at epoch {X} due to numerical overflow of the loss function.”

• Several new SGD optimizers were added: "ADAMw", "Adadelta", "Adagrad", and "RMSprop".

• Mixture parameter values different than zero cannot be used for several optimizers since they require L2 penalties.

brulee 0.5.0

• Removed a unit test for numerical overflow since it occurs less frequently and has become increasingly more challenging to reproduce.

brulee 0.4.0

• Added a convenience function, brulee_mlp_two_layer(), to more easily fit two-layer networks with parsnip.

• Various changes and improvements to error and warning messages.

• Fixed a bug that occurred when linear activation was used for neural networks (#68).

brulee 0.3.0

• Fixed bug where coef() didn’t would error if used on a brulee_logistic_reg() that was trained with a recipe. (#66)

• Fixed a bug where SGD always being used as the optimizer (#61).

• Additional activation functions were added (#74).

brulee 0.2.0

• Several learning rate schedulers were added to the modeling functions (#12).

• An optimizer was added to [brulee_mlp()], with a new default being LBFGS instead of stochastic gradient descent.

brulee 0.1.0

• Modeling functions gained a mixture argument for the proportion of L1 penalty that is used. (#50)

• Penalization was not occurring when quasi-Newton optimization was chosen. (#50)

brulee 0.0.1

First CRAN release.