From c67b38dccc59f96e41ed503ec95e0f7505ec0153 Mon Sep 17 00:00:00 2001 From: kwinkunks Date: Mon, 25 Sep 2023 21:57:06 +0200 Subject: [PATCH] Bits for multimodality detector --- CHANGELOG.md | 5 +++-- src/redflag/sklearn.py | 2 +- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 6575144..4fd3c11 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,10 +1,11 @@ # Changelog -## 0.3.1, Fall 2023 +## 0.3.1, coming Fall 2023 +- `redflag` can now be installed by the `conda` package and environment manager. To do so, use `conda install -c conda-forge redflag`. - All of the `sklearn` components can now be instantiated with `warn=False` in order to trigger a `ValueException` instead of a warning. This allows you to build pipelines that will break if a detector is triggered. - You can now pass `groups` to `redflag.distributions.is_multimodal()`. If present, the modality will be checked for each group, returning a Boolean array of values (one for each group). This allows you to check a feature partitioned by target class, for example. -- Added `MultimodalDetector` to provide a way to check for multimodal features. If `y` is passed and is categorical, it will be used to partition the data and modality will be checked for each class. +- Added `MultimodalityDetector` to provide a way to check for multimodal features. If `y` is passed and is categorical, it will be used to partition the data and modality will be checked for each class. - Removed `RegressionMultimodalDetector`. Use `MultimodalDetector` instead. diff --git a/src/redflag/sklearn.py b/src/redflag/sklearn.py index a6cc727..3f0a75f 100644 --- a/src/redflag/sklearn.py +++ b/src/redflag/sklearn.py @@ -1014,7 +1014,7 @@ def make_rf_pipeline(*steps, memory=None, verbose=False): ("rf.imbalance", ImbalanceDetector()), ("rf.clip", ClipDetector()), ("rf.correlation", CorrelationDetector()), - # ("rf.multimodal", MultimodalDetector()), + ("rf.multimodality", MultimodalityDetector()), ("rf.outlier", OutlierDetector()), ("rf.distributions", DistributionComparator()), ("rf.importance", ImportanceDetector()),