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RcppML 0.5.0

Major changes

  • Launch pkgdown site
  • Added the nmf S3 class to the result of nmf function
  • Introduce S3 methods for NMF ([, align, biplot, dim, dimnames, head, mse, predict, print, prod, sort, sparsity, summary, t)
  • New plotting methods for NMF (biplot.nmf, plot.nmfSummary, plot.nmfCrossValidation)
  • mse is now an S3 method for nmf objects
  • project now handles only projections of w, for simplicity
  • New vignette on Getting Started with NMF!

Minor changes

  • Support for specific sample and feature selections for NMF removed to increase performance on C++ end
  • Removed updateInPlace advanced parameter for nmf because advantages were not convincing
  • mask_zeros implementation is now specific to sparse matrices, multi-thread parallelization, and projections with transposition
  • Added cosine function for fast cosine distance calculations
  • Condensed and pared down documentation throughout. Advanced usage discussion will be moved to future vignettes.

RcppML 0.5.1

Major changes

  • three new datasets (hawaiibirds, aml, and movielens)
  • Move NMF models and methods from S3 to S4 for stability
  • Better random initializations (now using both rnorm and runif with multiple ranges/shapes, when multiple seeds are specified)
  • added L2 regularization to NMF
  • Support for masking values
  • add impute and perturb methods to crossValidate

Minor changes

  • better random initializations (now using both rnorm and runif with multiple ranges/shapes)
  • New vignette on random restarts
  • better "head" and "show" methods
  • return "w_init" with model

RcppML 0.5.2

Major changes

  • add linked NMF
  • update all documentation

Minor changes

  • clean up C++ API
  • C++ API gets meta-templating

RcppML 1.0

Major changes:

  • better cross-validation, now exclusively using the mean squared error of missing value imputation (random speckled patterns of missing values)
  • complete migration to the S4 system, with backwards compatibility for CRAN version 0.5.0
  • new vignettes and built-in datasets

Minor changes:

  • compatibility with latest version of the Matrix package