MeasureClassifF1
with MeasureClassifFScore
and fixed a bug in the
F1 performance calculation (#353). Thanks to @001ben for reporting.It is now possible to predict and score results on the training set or on both
training and test set.
Learners can be instructed to predict on multiple sets by setting
predict_sets
(default: "test"
). Measures operate on all sets specified in
their field predict_sets
(default: "test"
.
ResampleResult$prediction
and ResampleResult$predictions()
are now methods
instead of fields, and allow to extract predictions for different predict
sets.
ResampleResult$performance()
has been renamed to ResampleResult$score()
for consistency.
BenchmarkResult$performance()
has been renamed to BenchmarkResult$score()
for consistency.
Changed API for (internal) constructors accepting paradox::ParamSet()
.
Instead of passing the initial values separately, the initial values must now
be set directly in the ParamSet
.
Deprecated support of automatically creating objects from strings.
Instead, mlr3
provides the following helper functions intended to ease the
creation of objects stored in dictionaries:
tsk()
, tgen()
, lrn()
, rsmp()
, msr()
.
BenchmarkResult
now ensures that the stored ResampleResult
s are in a
persistent order. Thus, ResampleResult
s can now be addressed by their
position instead of their hash.
New field BenchmarkResult$n_resample_results
.
New field BenchmarkResult$hashes
.
New method Task$rename()
.
New S3 generic as_benchmark_result()
.
Renamed Generator
to TaskGenerator
.
Removed the control object mlr_control()
.
Removed ResampleResult$combine()
.
Removed BenchmarkResult$best()
.
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