mlr3pipelines 0.11.0

• Fix: Made FilterEnsemble tests deterministic and more robust.
• Fix: Made tests for PipeOpLearnerCV deterministic.
• feat: All imputation PipeOps now support feature types Date and POSIXct.
• Fix: PipeOpTextVectorizer now uses coercion to TsparseMatrix instead of deprecated dgTMatrix to avoid Matrix deprecation warnings.
• New method $predict_newdata_fast() for GraphLearner. Note that currently this is only a thin wrapper around $predict_newdata() to maintain compatibility, but in the future it may get optimized to enable faster predictions on new data.
• feat: PipeOpRenameColumns's hyperparameter renaming can now also take a function transforming old column names to new column names.
• feat: Added new hyperparameters filter_score_transform, result_score_transform, and aggregator to FilterEnsemble. BREAKING CHANGE: The default behavior for handling NA scores in the aggregation has changed. Previously, NA scores were simply ignored and weights were not changed. Now, weighted.mean is used, which normalizes the weights for all non-NA scores.
• feat: Added new hyperparameters weights_learner and weights_measure to PipeOpClassWeights to allow specification which type of weight column to add to the Task.
• New PipeOp PipeOpClassWeightEx extends the functionality of PipeOpClassWeights to also support multiclass classification tasks as well as several methods of automatically determining weights based on the target class of a sample.
• New PipeOp PipeOpSplines that expands numeric features into spline basis columns.