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src/Makevars / src/Makevars.win
linking the numerical kernels against R’s BLAS/LAPACK
($(LAPACK_LIBS) $(BLAS_LIBS) $(FLIBS)). Without the
explicit link line the Armadillo calls (dgemm_,
dgemv_, ddot_, dsyrk_, …) were
left undefined at link time on the CRAN Windows builder. No user-visible
changes.torch. Forward
propagation, backpropagation and Adam optimization are now implemented
natively in C++ via RcppArmadillo, with hand-derived
closed-form gradients. The torch (and transitive
libtorch) dependency is gone, so the package installs and
trains without downloading a deep-learning runtime. ggplot2
is likewise no longer a dependency; plotting uses base graphics.task = "survival": train against a
survival::Surv(time, event) outcome with either
loss = "cox" (batch-wise Breslow-tie Cox partial
likelihood, the default) or loss = "brier" (discrete-time
hazard head trained on the IPCW integrated Brier score).
predict(type = "survival") returns the survival-probability
curve for Brier-loss models; densemlp_metrics() reports
Harrell’s concordance index;
densemlp_integrated_brier_score() evaluates a Brier-loss
model’s IBS on new data.densemlp(formula = y ~ ., data = df)
(including survival::Surv(time, status) ~ .) as an
alternative to x/y. It must be passed by name,
since x/y keep the first two positional
slots.residual, gated, learned cross-feature
interaction, exponential moving-average weights
(ema_decay), learning-rate schedules
(lr_schedule), internal bootstrap ensembles
(ensemble, ncores) and a
tune_densemlp() grid search.batch_norm (default TRUE): set to
FALSE for Linear -> ReLU hidden blocks with
no normalization and no BN affine parameters.input_projection: an optional bare linear layer
mapping the encoded predictors to a chosen dimension before the first
hidden block. Cannot be combined with interaction.task now accepts "binary" and
"multiclass" explicitly (in addition to
"regression", "survival" and the default
"auto").torch-era arguments that no longer apply:
activation, optimizer,
weight_decay and input_projection’s old list
form. The fitted object’s class is now "densemlp" (was
"densemlp_fit"), and its autoplot() method is
replaced by plot() / plot_history().perm_importance() (model-agnostic permutation
importance, now also covering survival) and plot_history()
are kept, on the new backend.cv_densemlp(): k-fold cross-validation with the
same formula/x-y interface and task-aware defaults as
densemlp() / tune_densemlp().Authors@R.NEWS.md was kept prior to this
version; see the git history for the earlier development log.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.