- Bug fixes
- New CRAN version
- Internal changes (slightly improved computation speed)
- Warning: Possible seed differences compared to older versions
- Bug fixes
- Add support of splitting weights for corrected impurity importance
- Bug fixes
- Add inbag argument for manual selection of observations in trees
- Bug fixes
- Add max.depth parameter to limit tree depth
- Bug fixes
- New CRAN version
- Remove GenABEL from suggested packages (removed from CRAN). GenABEL data is still supported
- Improve memory management (internal changes)
- Add impurity importance for the maxstat splitting rule
- Bug fixes
- Add 'order' mode for unordered factors for GenABEL SNP data (binary classification and regression)
- Bug fixes
- Change license of C++ core to MIT (R package is still GPL3)
- Better 'order' mode for unordered factors for multiclass and survival
- Bug fixes
- Add class-weighted Gini splitting
- Bug fixes
- Add fixed proportion sampling
- Bug fixes
- New CRAN version
- Faster aggregation of predictions
- Fix memory issues on Windows 7
- Add treeInfo() function to extract human readable tree structure
- Add quantile prediction as in quantile regression forests
- Add standard error estimation with the infinitesimal jackknife (now the default)
- Add bias-corrected impurity importance (actual impurity reduction, AIR)
- Add impurity importance for survival forests
- Bug fixes
- New CRAN version
- 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
- New CRAN version
- Improvements in holdoutRF and importance p-value estimation
- Split at mid-point between candidate values
- Better formula interface: Support interactions terms and faster computation
- Add randomized splitting (extraTrees)
- Bug fixes
- Drop unused factor levels in outcome before growing
- Add predict.all for probability and survival prediction
- Bug fixes
- New CRAN version
- Faster version of getTerminalNodeIDs(), included in predict()
- Handle new factor levels in 'order' mode
- Bug fixes
- Set write.forest=TRUE by default
- Add num.trees option to predict()
- Bug fixes
- Bug fixes
- Use unadjusted p-value for 2 categories in maxstat splitting
- Bug fixes
- New CRAN version
- Add splitting by maximally selected rank statistics for regression forests
- Bug fixes
- Use faster method for unordered factor splitting
- Add p-values for variable importance
- Bug fixes
- Add splitting by maximally selected rank statistics for survival forests
- Bug fixes
- Add Windows multithreading support for new toolchain
- Runtime improvement for regression forests on classification data
- New CRAN version. New CRAN versions will be 0.x.0, development versions 0.x.y
- Reduce memory usage of savest forest objects (changed child.nodeIDs interface)
- Remove tuning functions, please use mlr or caret
- Fix bug with alternative interface and prediction
- Small fixes
- 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
- Small changes in documentation
- Add case-specific random forests
- Add case weights (weighted bootstrapping or subsampling)
- Catch error of outdated gcc not supporting C++11 completely
- 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
- Small fixes for Solaris compiler
- Add C-index splitting
- Fix NA SNP handling
- Fix matrix and gwaa alternative survival interface
- Version submitted to JSS
- Small changes in documentation
- Preallocate memory for splitting
- Remove recursive splitting
- Allow matrix as input data in R version
- Fix prediction of classification forests in R
- 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
- Fix problems when using Rcpp <0.11.4
- Add option to split on unordered categorical covariates
- Optimize memory management for very large survival forests
- 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
- 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.
- Windows support for R version (without multithreading)
- 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