##### Version 0.16.0 * Add node.stats option to save node statistics of all nodes * Add time.interest option to restrict unique survival times (faster and saves memory) * Fix min bucket option in C++ version * Fix memory error for always.split.variables in certain settings * Fix quantile regression for factor variables in "order" mode ##### Version 0.15.0 * Switch to C++14 standard * Add min.bucket parameter to restrict terminal node size * Fix a bug with always.split.variables selecting the wrong variables ##### Version 0.14.0 * Faster permutation variable importance for high dimensional data (thanks to Roman Hornung) * Add deforest() function to remove trees from ensemble * Allow split.select.weights and always.split.variables together * Add as.data.frame() method for predictions * Fix weight calculation in case-specific RF (csrf()) * Fix cross compiling for Windows ##### Version 0.13.0 * Faster quantile prediction * Add ... argument to ranger() * Bug fixes ##### Version 0.12.0 * Faster computation (in some cases) * Add local variable importance * Add "hellinger" splitrule for binary classification * Add "beta" splitrule for bounded outcomes * Accept user-specified function in quantile prediction * Add regularization * Add x/y interface * Internal changes (seed differences possible, prediction incompatible with older versions) * Bug fixes ##### Version 0.11.0 * Add max.depth parameter to limit tree depth * Add inbag argument for manual selection of observations in trees * Add support of splitting weights for corrected impurity importance * Internal changes (slightly improved computation speed) * Warning: Possible seed differences compared to older versions * Bug fixes ##### Version 0.10.0 * Change license of C++ core to MIT (R package is still GPL3) * Better 'order' mode for unordered factors for multiclass and survival * Add 'order' mode for unordered factors for GenABEL SNP data (binary classification and regression) * Add class-weighted Gini splitting * Add fixed proportion sampling * Add impurity importance for the maxstat splitting rule * Remove GenABEL from suggested packages (removed from CRAN). GenABEL data is still supported * Improve memory management (internal changes) * Bug fixes ##### Version 0.9.0 * Add bias-corrected impurity importance (actual impurity reduction, AIR) * Add quantile prediction as in quantile regression forests * Add treeInfo() function to extract human readable tree structure * Add standard error estimation with the infinitesimal jackknife (now the default) * Add impurity importance for survival forests * Faster aggregation of predictions * Fix memory issues on Windows 7 * Bug fixes ##### Version 0.8.0 * Handle sparse data of class Matrix::dgCMatrix * Add prediction of standard errors to predict() * Allow devtools::install_github() without subdir and on Windows * Bug fixes ##### Version 0.7.0 * Add randomized splitting (extraTrees) * Better formula interface: Support interactions terms and faster computation * Split at mid-point between candidate values * Improvements in holdoutRF and importance p-value estimation * Drop unused factor levels in outcome before growing * Add predict.all for probability and survival prediction * Bug fixes ##### Version 0.6.0 * Set write.forest=TRUE by default * Add num.trees option to predict() * Faster version of getTerminalNodeIDs(), included in predict() * Handle new factor levels in 'order' mode * Use unadjusted p-value for 2 categories in maxstat splitting * Bug fixes ##### Version 0.5.0 * Add Windows multithreading support for new toolchain * Add splitting by maximally selected rank statistics for survival and regression forests * Faster method for unordered factor splitting * Add p-values for variable importance * Runtime improvement for regression forests on classification data * Bug fixes ##### Version 0.4.0 * Reduce memory usage of savest forest objects (changed child.nodeIDs interface) * Add keep.inbag option to track in-bag counts * Add option sample.fraction for fraction of sampled observations * Add tree-wise split.select.weights * Add predict.all option in predict() to get individual predictions for each tree for classification and regression * Add case-specific random forests * Add case weights (weighted bootstrapping or subsampling) * Remove tuning functions, please use mlr or caret * Catch error of outdated gcc not supporting C++11 completely * Bug fixes ##### Version 0.3.0 * Allow the user to interrupt computation from R * Transpose classification.table and rename to confusion.matrix * Respect R seed for prediction * Memory improvements for variable importance computation * Fix bug: Probability prediction for single observations * Fix bug: Results not identical when using alternative interface ##### Version 0.2.7 * Small fixes for Solaris compiler ##### Version 0.2.6 * Add C-index splitting * Fix NA SNP handling ##### Version 0.2.5 * Fix matrix and gwaa alternative survival interface * Version submitted to JSS ##### Version 0.2.4 * Small changes in documentation ##### Version 0.2.3 * Preallocate memory for splitting ##### Version 0.2.2 * Remove recursive splitting ##### Version 0.2.1 * Allow matrix as input data in R version ##### Version 0.2.0 * Fix prediction of classification forests in R ##### Version 0.1.9 * Speedup growing for continuous covariates * Add memory save option to save memory for very large datasets (but slower) * Remove memory mode option from R version since no performance gain ##### Version 0.1.8 * Fix problems when using Rcpp <0.11.4 ##### Version 0.1.7 * Add option to split on unordered categorical covariates ##### Version 0.1.6 * Optimize memory management for very large survival forests ##### Version 0.1.5 * Set required Rcpp version to 0.11.2 * Fix large $call objects when using BatchJobs * Add details and example on GenABEL usage to documentation * Minor changes to documentation ##### Version 0.1.4 * Speedup for survival forests with continuous covariates * R version: Generate seed from R. It is no longer necessary to set the seed argument in ranger calls. ##### Version 0.1.3 * Windows support for R version (without multithreading) ##### Version 0.1.2 * Speedup growing of regression and probability prediction forests * Prediction forests are now handled like regression forests: MSE used for prediction error and permutation importance * Fixed name conflict with randomForest package for "importance" * Fixed a bug: prediction function is now working for probability prediction forests * Slot "predictions" for probability forests now contains class probabilities * importance function is now working even if randomForest package is loaded after ranger * Fixed a bug: Split selection weights are now working as expected * Small changes in documentation