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ppl("convert_types")
.inst/
. These are considered experimental and unstable.PipeOpFeatureUnion
used in ppl("robustify")
and ppl("stacking")
.pipeline_bagging()
gets the replace
argument (old behaviour FALSE
by default).$add_pipeop()
method got an argument clone
(old behaviour TRUE
by default).PipeOpFeatureUnion
in some rare cases dropped variables called "x"
.ppl("robustify")
pipelines.PipeOpTuneThreshold
was not overloading the correct .train
and .predict
functions.$hash
and $phash
for GraphLearner
and all PipeOp
s. This could break users that inherit from PipeOp
and make use of $hash
in the future (but is ultimately in their interest!).phash
of GraphLearner
now considers content of Graph, not only IDs.po()
, pos()
can now construct PipeOp
s with ID postfix _<number>
to avoid ID clashes.GraphLearner
now has method $base_learner()
that returns the underlying Learner
, if it can be found by a simple heuristic.PipeOpHistBin
operation.PipeOpPCA
documentation of center
default.$label
active binding, setting it to the help()
-page title by default.$help()
function for all PipeOps as well as Graph
, GraphLearner
and all Learners.GraphLearner
can be created without cloning Graph
(for internal use).predict.Graph
throws helpful error when it cannot create a fitting Task
.PipeOpLearner
packages
slot is set to the Learner
’s packages
.PipeOp
train()
and predict()
report correct channel name when output has wrong type.%>>!%
that modifies Graphs in-place.chain_graphs()
, concat_graphs()
, Graph$chain()
as alternatives for %>>%
and %>>!%
.pos()
and ppls()
which create lists of PipeOps/Graphs and can be seen as “plural” forms of po()
and ppl()
.po()
S3-method for PipeOp
class that clones a PipeOp object and optionally modifies its attributes.Graph$add_pipeop()
now clones the PipeOp being added.graph_model
in GraphLearner
class, which gets the trained Graph.as_learner()
S3-method for PipeOp
class that wraps a PipeOp
in a Graph
and turns that into a Learner
.PipeOpHistBin
: renamed bins
Param to breaks
PipeOpImputeHist
: fix handling of integer features spanning the entire represented integer rangePipeOpImputeOOR
: fix handling of integer features spanning the entire represented integer rangePipeOpProxy
: Avoid unnecessary clonePipeOpScale
: Performance improvementbbotk
version.mlr_graphs
: pipeline_stacking
mlr3
version.PipeOpFilter
gets additional filter.permuted
hyperparameter.add_edge
of Graphs work with Multiplicities.GraphLearner
hash depend on id
.LearnerAvg
.mlr3
version.bbotk
0.3.0as.data.table(mlr_pipeops)
work with paradox
0.6PipeOpColApply
: now allows for an applicator function with multiple columns as a return value; also inherits from PipeOpTaskPreprocSimple
nowPipeOpMissInd
now also allows for setting type = integerPipeOpNMF
: now exposes all parameters previously in .options
mlr_graphs
:
pipeline_bagging
now uses multiplicities internallypipeline_robustify
determines the type of newly created columns when using PipeOpMissInd
PipeOpFeatureUnion
: Fixed a minor bug when checking for duplicatesexpect_valid_pipeop_param_set
GraphLearner
GraphLearner
allows custom id
mlr3
0.6NULL
input channels accept any kind of inputprint()
method of Graphs now also allows for printing a DOT representation on the consolestate
of PipeOps is now reset to NULL
when training failsas_learner.PipeOp
LearnerClassifAvg
, LearnerRegrAvg
use bbotk
nowppl_robustify
detects whether a learner can handle factorsPipeOpTextVectorizer
can now return an “integer sequence representation”.PipeOpNMF
PipeOpColRoles
PipeOpVtreat
mlr_graphs
:
pipeline_bagging
pipeline_branch
pipeline_greplicate
pipeline_robustify
pipeline_targettrafo
pipeline_ovr
PipeOpOVRSplit
, PipeOpOVRUnite
PipeOpReplicate
PipeOpMultiplicityExply
, PipeOpMultiplicityImply
PipeOpTargetTrafo
, PipeOpTargetInvert
PipeOpTargetMutate
PipeOpTargetTrafoScaleRange
PipeOpProxy
PipeOpDateFeatures
PipeOpImputeConstant
PipeOpImputeLearner
PipeOpMode
PipeOpRandomResponse
PipeOpRenameColumns
PipeOpTextVectorizer
PipeOpThreshold
PipeOpImputeNewlvl
–> PipeOpImputeOOR
(with additional functionality for continuous values)PipeOpFeatureUnion
: Bugfix: avoid silently overwriting features when names clashPipeOpHistBin
: Bugfix: handle test set data out of training set rangePipeOpLearnerCV
: Allow returning trainingset prediction during train()
PipeOpMutate
: Allow referencing newly created columnsPipeOpScale
: Allow robust scalingPipeOpLearner
, PipeOpLearnerCV
: learner_models
for access to learner with model slotselector_missing
selector_cardinality_greater_than
%>>%
PipeOpTaskPreproc
now has feature_types
slotPipeOpTaskPreproc(Simple)
internal API changed: use .train_task()
, .predict_task()
, .train_dt()
, .predict_dt()
, .select_cols()
, .get_state()
, .transform()
, .get_state_dt()
, .transform_dt()
instead of the old methods without dot prefix.train()
, .predict()
instead of train_internal()
, predict_internal()
Graph
new method update_ids()
Graph
methods train(single_input = FALSE)
and predict(single_input = FALSE)
now handle vararg channels correctly.greplicate()
; use pipeline_greplicate
/ ppl("greplicate")
instead.po()
now automatically converts Selector
to PipeOpSelect
po()
prints available mlr_pipeops
dictionary contentmlr_graphs
dictionary of useful Graphs, with short form accessor ppl()
mlr3
version 0.4.0stringsAsFactors
option default change in 3.6 -> 4.0)predict()
generic for GraphsaveRDS()
, serialize()
etc.mlr3
version 0.1.5 (handling of character columns changed)PipeOpEncodeImpact
PipeOpEncode
: handle NAsThese 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.