densemlp 0.7.1

• Add 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.

densemlp 0.7.0

Backend rewrite

• The model backend no longer uses 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.

New capabilities

• 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.
• Formula interface: 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.

Argument changes

• New batch_norm (default TRUE): set to FALSE for Linear -> ReLU hidden blocks with no normalization and no BN affine parameters.
• New 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").
• Removed the 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().

Retained helpers

• perm_importance() (model-agnostic permutation importance, now also covering survival) and plot_history() are kept, on the new backend.

densemlp 0.6.0

• New cv_densemlp(): k-fold cross-validation with the same formula/x-y interface and task-aware defaults as densemlp() / tune_densemlp().
• Standardized the maintainer’s family-name casing to “El Badisy” in Authors@R.

densemlp 0.5.0

• First CRAN release. No NEWS.md was kept prior to this version; see the git history for the earlier development log.