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PipeOpRowApply
/
po("rowapply")
PipeOp
IDs now explicitly forbidden.GraphLearner$base_learner()
now works with
PipeOpBranch
, and is generally more robust.GraphLearner
now supports $importance
,
$selected_features()
, $oob_error()
, and
$loglik()
. These are computed from the underlying
Learner
.GraphLearner$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
and PipeOpTuneThreshold
now have the $predict_type
"prob"
. They can be
set to "response"
, in which case the probability
predictions are discarded, potentially saving memory.Graph$tran()
/ Graph$predict()
with single_input = FALSE
now correctly handles
PipeOp
s with multiple inputs.PipeOpImputeOOR
now retains the
.MISSING
level in factors during prediction that were
imputed during training, but had no missing values during
prediction.as_data_table(po())
now works even when some
PipeOp
s can not be constructed. For these
PipeOp
s, NA
is reported in most columns.PipeOpRowApply
/
po("rowapply")
PipeOpADAS
/
po("adas")
and PipeOpBLSmote
/
po("blsmote")
PipeOpSmoteNC
/ po("smotenc")
CnfFormula
and other Cnf*
objects.mlr3
release.bbotk
release.GraphLearner
ppl("convert_types")
.inst/
. These are
considered experimental and unstable.PipeOpFeatureUnion
used in
ppl("robustify")
and ppl("stacking")
.pipeline_bagging()
gets the replace
argument (old behaviour FALSE
by default).$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.