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Performance improved. R interface and C++ core have been separated.
Depends
to R >= 3.6.0.19e7c475
and inlining access to data. 233063e0
.DataVector
class to read, write, and pass data without
R.New feature! literanger can now serialize trained random forests using cereal.
The project has been moved to GitLab: https://gitlab.com/stephematician/literanger.
predict
now matches the
response type in training ea67c83e
read_literanger
and
write_literanger
for serialization.names_of_always_draw
argument 6d31d7f3
9a3b639a
in particular for ‘maxstat’ 37580d9b
Update to pass CRAN’s ASAN check
d3f6424
)d7f058d
)91b6c6d
,
0f62d02
)b6df5d9
)First release
A refactoring and adaptation of the ranger package https://github.com/imbs-hl/ranger for random forests. Has faster prediction mode intended for embedding into the multiple imputation algorithm proposed by Doove et al in:
Doove, L. L., Van Buuren, S., & Dusseldorp, E. (2014). Recursive partitioning for missing data imputation in the presence of interaction effects. Computational statistics & data analysis, 72, 92-104.
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.