Releases: mlr-org/mlr3pipelines
Releases · mlr-org/mlr3pipelines
mlr3pipelines 0.7.0
- New PipeOp
PipeOpRowApply
/po("rowapply")
- Empty
PipeOp
IDs now explicitly forbidden. - Bugfix:
Graph$tran()
/Graph$predict()
withsingle_input = FALSE
now correctly handlesPipeOp
s with multiple inputs. GraphLearner$base_learner()
now works withPipeOpBranch
, and is generally more robust.GraphLearner
now supports$importance
,$selected_features()
,$oob_error()
, and$loglik()
.
These are computed from the underlyingLearner
.GraphLearner$impute_selected_features
option added:
$selected_features()
is reported even if the underlying base learner does not report it; in this case, the full feature set as seen by that learner is returned.GraphLearner$predict_type
handling more robust now.PipeOpThreshold
andPipeOpTuneThreshold
now have the$predict_type
"prob"
.
They can be set to"response"
, in which case the probability predictions are discarded, potentially saving memory.- Bugfix for handling multiplicities in PipeOps with vararg channels.
- Bugfix:
PipeOpImputeOOR
now retains the.MISSING
level in factors during prediction that were imputed during training, but had no missing values during prediction. as_data_table(po())
now works even when somePipeOp
s can not be constructed.
For thesePipeOp
s,NA
is reported in most columns.- Compatibility with upcoming
mlr3
release. - New PipeOps for handling inbalanced data:
PipeOpADAS
/po("adas")
,PipeOpBLSmote
/po("blsmote")
andPipeOpSmoteNC
/po("smotenc")
mlr3pipelines 0.6.0
- Compatibility with new
bbotk
release. - Added marshaling support to
GraphLearner
- Support internal tuning and validation
mlr3pipelines 0.1.2
- Work with new mlr3 version 0.1.5 (handling of character columns changed)
mlr3pipelines 0.1.1
- Better html graphics for linear Graphs
- New PipeOps:
- PipeOpEncodeImpact
- Changed PipeOp Behaviour:
- PipeOpEncode: handle NAs
mlr3pipelines 0.1.0
Initial upload to CRAN.