# CapyMOA

> # [CapyMOA](https://capymoa.org)
> 
> ![Banner Image](https://github.com/adaptive-machine-learning/CapyMOA/raw/main/docs/images/CapyMOA.jpeg)
> 
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> 
> 
> **CapyMOA does efficient machine learning for data streams in Python**. A data stream is
> a sequence of items that arrive one by one and are too large or urgent to process
> offline. CapyMOA is a toolbox of methods and evaluators for: classification, regression,
> clustering, anomaly detection, semi-supervised learning, online continual learning, and
> drift detection for data streams.
> 
> To install:
> 
> ```
> pip install capymoa
> ```
> 
> The deep-learning parts of CapyMOA (`capymoa.ocl`, `capymoa.core.torch.ann`, the `Batch*`
> learners) need PyTorch, which is an optional extra:
> 
> ```
> pip install capymoa[torch]
> ```
> 
> Refer to the [Setup](https://capymoa.org/setup) guide for other options,
> including CPU-only PyTorch and dev dependencies.
> 
> ```python
> from capymoa.datasets import Electricity
> from capymoa.classifier import HoeffdingTree
> from capymoa.evaluation import prequential_evaluation
> 
> # 1. Load a streaming dataset
> stream = Electricity()
> 
> # 2. Create a machine learning model
> model = HoeffdingTree(stream.get_schema())
> 
> # 3. Run with test-then-train evaluation
> results = prequential_evaluation(stream, model)
> 
> # 4. Success!
> print(f"Accuracy: {results.accuracy():.2f}%")
> ```
> 
> Next, we recommend the [Tutorials](https://capymoa.org/tutorials).
> 
> > **⚠️ WARNING**
> >
> > CapyMOA is still in the early stages of development. The API is subject to
> > change until version 1.0.0. If you encounter any issues, please report
> > them in [GitHub Issues](https://github.com/adaptive-machine-learning/CapyMOA/issues)
> > or talk to us on [Discord](https://discord.gg/spd2gQJGAb).
> 
> ---
> 
> ![Benchmark Image](https://github.com/adaptive-machine-learning/CapyMOA/raw/main/docs/images/arf100_cpu_time.png)
> Benchmark comparing CapyMOA against other data stream libraries. The benchmark
> was performed using an ensemble of 100 ARF learners trained on
> the `capymoa.datasets.RTG_2abrupt` dataset containing 100,000 samples and 30
> features.  You can find the code to reproduce this benchmark in
> [`benchmarks/README.md`](benchmarks/README.md), with the runnable script at
> [`benchmarks/benchmarking.py`](benchmarks/benchmarking.py).
> *CapyMOA has the speed of MOA with the flexibility of Python and the richness of
> Python's data science ecosystem.*
> 
> ## Cite Us 
> 
> If you use CapyMOA in your research, please cite us using the following BibTeX item.
> ``` 
> @misc{gomes2025,
>   title={{CapyMOA}: Efficient Machine Learning for Data Streams and Online Continual Learning in Python},
>   author={Heitor Murilo Gomes and Anton Lee and Nuwan Gunasekara and Yibin Sun and Guilherme Weigert Cassales and Justin Jia Liu and Marco Heyden and Vitor Cerqueira and Maroua Bahri and Yun Sing Koh and Bernhard Pfahringer and Albert Bifet},
>   year={2025},
>   eprint={2502.07432},
>   archivePrefix={arXiv},
>   primaryClass={cs.LG},
>   url={https://arxiv.org/abs/2502.07432}
> }
> ```


2026 CapyMOA Developers

## Pages in this subsection

- [`classifier`](capymoa.classifier.md): Classification.
- [`CSMOTE`](capymoa.classifier.CSMOTE.md): Bases: `MOAClassifier`
- [`EFDT`](capymoa.classifier.EFDT.md): Bases: `MOAClassifier`
- [`KNN`](capymoa.classifier.KNN.md): Bases: `MOAClassifier`
- [`LAST`](capymoa.classifier.LAST.md): Bases: `MOAClassifier`
- [`PLASTIC`](capymoa.classifier.PLASTIC.md): Bases: `MOAClassifier`
- [`AdaptiveRandomForestClassifier`](capymoa.classifier.AdaptiveRandomForestClassifier.md): Bases: `MOAClassifier`
- [`DynamicEnsembleMemberSelection`](capymoa.classifier.DynamicEnsembleMemberSelection.md): Bases: `MOAClassifier`
- [`DynamicWeightedMajority`](capymoa.classifier.DynamicWeightedMajority.md): Bases: `MOAClassifier`
- [`Finetune`](capymoa.classifier.Finetune.md): Bases: `BatchClassifier`
- [`HoeffdingAdaptiveTree`](capymoa.classifier.HoeffdingAdaptiveTree.md): Bases: `HoeffdingTree`
- [`HoeffdingTree`](capymoa.classifier.HoeffdingTree.md): Bases: `MOAClassifier`
- [`LeveragingBagging`](capymoa.classifier.LeveragingBagging.md): Bases: `MOAClassifier`
- [`MajorityClass`](capymoa.classifier.MajorityClass.md): Bases: `MOAClassifier`
- [`NaiveBayes`](capymoa.classifier.NaiveBayes.md): Bases: `MOAClassifier`
- [`NoChange`](capymoa.classifier.NoChange.md): Bases: `MOAClassifier`
- [`OnlineAdwinBagging`](capymoa.classifier.OnlineAdwinBagging.md): Bases: `MOAClassifier`
- [`OnlineBagging`](capymoa.classifier.OnlineBagging.md): Bases: `MOAClassifier`
- [`OnlineSmoothBoost`](capymoa.classifier.OnlineSmoothBoost.md): Bases: `MOAClassifier`
- [`OzaBoost`](capymoa.classifier.OzaBoost.md): Bases: `MOAClassifier`
- [`PassiveAggressiveClassifier`](capymoa.classifier.PassiveAggressiveClassifier.md): Bases: `SKClassifier`
- [`SAMkNN`](capymoa.classifier.SAMkNN.md): Bases: `MOAClassifier`
- [`SGDClassifier`](capymoa.classifier.SGDClassifier.md): Bases: `SKClassifier`
- [`ShrubsClassifier`](capymoa.classifier.ShrubsClassifier.md): Bases: `_ShrubEnsembles`, `Classifier`
- [`StochasticGradientTree`](capymoa.classifier.StochasticGradientTree.md): Bases: `MOAClassifier`
- [`StreamingGradientBoostedTrees`](capymoa.classifier.StreamingGradientBoostedTrees.md): Bases: `MOAClassifier`
- [`StreamingRandomPatches`](capymoa.classifier.StreamingRandomPatches.md): Bases: `MOAClassifier`
- [`WeightedkNN`](capymoa.classifier.WeightedkNN.md): Bases: `MOAClassifier`
- [`drift`](capymoa.drift.md): Drift detection.
- [`base_detector`](capymoa.drift.base_detector.md): | `BaseDriftDetector`   | Drift Detector                                              |
- [`BaseDriftDetector`](capymoa.drift.base_detector.BaseDriftDetector.md): Bases: `LearnerParamsMixin`, `ABC`
- [`MOADriftDetector`](capymoa.drift.base_detector.MOADriftDetector.md): Bases: `BaseDriftDetector`
- [`detectors`](capymoa.drift.detectors.md): Concept and data drift detectors.
- [`ABCD`](capymoa.drift.detectors.ABCD.md): Bases: `BaseDriftDetector`
- [`ADWIN`](capymoa.drift.detectors.ADWIN.md): Bases: `MOADriftDetector`
- [`BNDM`](capymoa.drift.detectors.BNDM.md): Bases: `BaseDataDriftDetector`
- [`CUSUM`](capymoa.drift.detectors.CUSUM.md): Bases: `MOADriftDetector`
- [`D3`](capymoa.drift.detectors.D3.md): Bases: `BaseDataDriftDetector`
- [`DDM`](capymoa.drift.detectors.DDM.md): Bases: `MOADriftDetector`
- [`EDDM`](capymoa.drift.detectors.EDDM.md): Bases: `MOADriftDetector`
- [`MMD`](capymoa.drift.detectors.MMD.md): Bases: `BaseDataDriftDetector`
- [`OPTWIN`](capymoa.drift.detectors.OPTWIN.md): Bases: `BaseDriftDetector`
- [`PSI`](capymoa.drift.detectors.PSI.md): Bases: `BaseDataDriftDetector`
- [`RDDM`](capymoa.drift.detectors.RDDM.md): Bases: `MOADriftDetector`
- [`SEED`](capymoa.drift.detectors.SEED.md): Bases: `MOADriftDetector`
- [`STEPD`](capymoa.drift.detectors.STEPD.md): Bases: `MOADriftDetector`
- [`STUDD`](capymoa.drift.detectors.STUDD.md): Bases: `BaseDriftDetector`
- [`AndersonDarling`](capymoa.drift.detectors.AndersonDarling.md): Bases: `BaseDataDriftDetector`
- [`BaseDataDriftDetector`](capymoa.drift.detectors.BaseDataDriftDetector.md): Bases: `BaseDriftDetector`
- [`ChiSquare`](capymoa.drift.detectors.ChiSquare.md): Bases: `BaseDataDriftDetector`
- [`CramerVonMises`](capymoa.drift.detectors.CramerVonMises.md): Bases: `BaseDataDriftDetector`
- [`DataDriftResult`](capymoa.drift.detectors.DataDriftResult.md): Bases: `object`
- [`EWMAChart`](capymoa.drift.detectors.EWMAChart.md): Bases: `MOADriftDetector`
- [`EnergyDistance`](capymoa.drift.detectors.EnergyDistance.md): Bases: `BaseDataDriftDetector`
- [`GeometricMovingAverage`](capymoa.drift.detectors.GeometricMovingAverage.md): Bases: `MOADriftDetector`
- [`HDDMAverage`](capymoa.drift.detectors.HDDMAverage.md): Bases: `MOADriftDetector`
- [`HDDMWeighted`](capymoa.drift.detectors.HDDMWeighted.md): Bases: `MOADriftDetector`
- [`Hellinger`](capymoa.drift.detectors.Hellinger.md): Bases: `BaseDataDriftDetector`
- [`JensenShannon`](capymoa.drift.detectors.JensenShannon.md): Bases: `BaseDataDriftDetector`
- [`KLDivergence`](capymoa.drift.detectors.KLDivergence.md): Bases: `BaseDataDriftDetector`
- [`KolmogorovSmirnov`](capymoa.drift.detectors.KolmogorovSmirnov.md): Bases: `BaseDataDriftDetector`
- [`PageHinkley`](capymoa.drift.detectors.PageHinkley.md): Bases: `MOADriftDetector`
- [`Wasserstein`](capymoa.drift.detectors.Wasserstein.md): Bases: `BaseDataDriftDetector`
- [`eval_detector`](capymoa.drift.eval_detector.md): | `DriftDetectionMetrics`   | Metrics for evaluating drift detection performance.             |
- [`DriftDetectionMetrics`](capymoa.drift.eval_detector.DriftDetectionMetrics.md): Bases: `object`
- [`EvaluateDriftDetector`](capymoa.drift.eval_detector.EvaluateDriftDetector.md): Bases: `object`
- [`regressor`](capymoa.regressor.md): Regression.
- [`ARFFIMTDD`](capymoa.regressor.ARFFIMTDD.md): Bases: `MOARegressor`
- [`FIMTDD`](capymoa.regressor.FIMTDD.md): Bases: `MOARegressor`
- [`ORTO`](capymoa.regressor.ORTO.md): Bases: `MOARegressor`
- [`SOKNL`](capymoa.regressor.SOKNL.md): Bases: `MOARegressor`
- [`SOKNLBT`](capymoa.regressor.SOKNLBT.md): Bases: `MOARegressor`
- [`AdaptiveRandomForestRegressor`](capymoa.regressor.AdaptiveRandomForestRegressor.md): Bases: `MOARegressor`
- [`FadingTargetMean`](capymoa.regressor.FadingTargetMean.md): Bases: `MOARegressor`
- [`KNNRegressor`](capymoa.regressor.KNNRegressor.md): Bases: `MOARegressor`
- [`NoChange`](capymoa.regressor.NoChange.md): Bases: `Regressor`
- [`PassiveAggressiveRegressor`](capymoa.regressor.PassiveAggressiveRegressor.md): Bases: `SKRegressor`
- [`SGDRegressor`](capymoa.regressor.SGDRegressor.md): Bases: `SKRegressor`
- [`ShrubsRegressor`](capymoa.regressor.ShrubsRegressor.md): Bases: `_ShrubEnsembles`, `Regressor`
- [`StochasticGradientTree`](capymoa.regressor.StochasticGradientTree.md): Bases: `MOARegressor`
- [`StreamingGradientBoostedRegression`](capymoa.regressor.StreamingGradientBoostedRegression.md): Bases: `MOARegressor`
- [`TargetMean`](capymoa.regressor.TargetMean.md): Bases: `MOARegressor`
- [`cluster`](capymoa.cluster.md): Clustering.
- [`ClusTree`](capymoa.cluster.ClusTree.md): Bases: `MOAClusterer`
- [`Clustream`](capymoa.cluster.Clustream.md): Bases: `MOAClusterer`
- [`Clustream_with_kmeans`](capymoa.cluster.Clustream_with_kmeans.md): Bases: `MOAClusterer`
- [`Denstream_with_dbscan`](capymoa.cluster.Denstream_with_dbscan.md): Bases: `MOAClusterer`
- [`anomaly`](capymoa.anomaly.md): Anomaly detection.
- [`datasets`](capymoa.anomaly.datasets.md): Collection of built in anomaly detection datasets.
- [`TinyBlobs`](capymoa.anomaly.datasets.TinyBlobs.md): Bases: `NumpyStream`
- [`AdaptiveIsolationForest`](capymoa.anomaly.AdaptiveIsolationForest.md): Bases: `AnomalyDetector`
- [`Autoencoder`](capymoa.anomaly.Autoencoder.md): Bases: `AnomalyDetector`
- [`HalfSpaceTrees`](capymoa.anomaly.HalfSpaceTrees.md): Bases: `MOAAnomalyDetector`
- [`IForestASD`](capymoa.anomaly.IForestASD.md): Bases: `AnomalyDetector`
- [`Loda`](capymoa.anomaly.Loda.md): Bases: `AnomalyDetector`
- [`OnlineIsolationForest`](capymoa.anomaly.OnlineIsolationForest.md): Bases: `AnomalyDetector`
- [`RSHash`](capymoa.anomaly.RSHash.md): Bases: `AnomalyDetector`
- [`RobustRandomCutForest`](capymoa.anomaly.RobustRandomCutForest.md): Bases: `AnomalyDetector`
- [`StreamRHF`](capymoa.anomaly.StreamRHF.md): Bases: `AnomalyDetector`
- [`StreamingIsolationForest`](capymoa.anomaly.StreamingIsolationForest.md): Bases: `AnomalyDetector`
- [`ocl`](capymoa.ocl.md): Online Continual Learning (OCL) module.
- [`datasets`](capymoa.ocl.datasets.md): Use built-in datasets for online continual learning.
- [`DomainCIFAR100`](capymoa.ocl.datasets.DomainCIFAR100.md): Bases: `_TorchVisionDownload`, `_BuiltInCIScenario`
- [`DomainCIFAR100ViT`](capymoa.ocl.datasets.DomainCIFAR100ViT.md): Bases: `SplitCIFAR100ViT`
- [`RotatedFashionMNIST`](capymoa.ocl.datasets.RotatedFashionMNIST.md): Bases: `_TorchVisionDownload`, `_BuiltInRotatedDomainScenario`
- [`RotatedMNIST`](capymoa.ocl.datasets.RotatedMNIST.md): Bases: `_TorchVisionDownload`, `_BuiltInRotatedDomainScenario`
- [`RotatedTinyMNIST`](capymoa.ocl.datasets.RotatedTinyMNIST.md): Bases: `_BuiltInRotatedDomainScenario`
- [`SplitCIFAR10`](capymoa.ocl.datasets.SplitCIFAR10.md): Bases: `_TorchVisionDownload`, `_BuiltInCIScenario`
- [`SplitCIFAR10ViT`](capymoa.ocl.datasets.SplitCIFAR10ViT.md): Bases: `SplitCIFAR100ViT`
- [`SplitCIFAR100`](capymoa.ocl.datasets.SplitCIFAR100.md): Bases: `_TorchVisionDownload`, `_BuiltInCIScenario`
- [`SplitCIFAR100ViT`](capymoa.ocl.datasets.SplitCIFAR100ViT.md): Bases: `_BuiltInCIScenario`
- [`SplitFashionMNIST`](capymoa.ocl.datasets.SplitFashionMNIST.md): Bases: `_TorchVisionDownload`, `_BuiltInCIScenario`
- [`SplitMNIST`](capymoa.ocl.datasets.SplitMNIST.md): Bases: `_TorchVisionDownload`, `_BuiltInCIScenario`
- [`TinySplitMNIST`](capymoa.ocl.datasets.TinySplitMNIST.md): Bases: `_BuiltInCIScenario`
- [`evaluation`](capymoa.ocl.evaluation.md): Evaluate online continual learning in classification tasks.
- [`events`](capymoa.ocl.evaluation.events.md): Event definitions for OCL evaluation loops.
- [`EvalBatchPredict`](capymoa.ocl.evaluation.events.EvalBatchPredict.md): Bases: `TestTaskBegin`
- [`TestBegin`](capymoa.ocl.evaluation.events.TestBegin.md): Bases: `Event`
- [`TestEnd`](capymoa.ocl.evaluation.events.TestEnd.md): Bases: `Event`
- [`TestTaskBegin`](capymoa.ocl.evaluation.events.TestTaskBegin.md): Bases: `Event`
- [`TestTaskEnd`](capymoa.ocl.evaluation.events.TestTaskEnd.md): Bases: `TestTaskBegin`
- [`TrainBatchPredict`](capymoa.ocl.evaluation.events.TrainBatchPredict.md): Bases: `TrainTaskBegin`
- [`TrainBegin`](capymoa.ocl.evaluation.events.TrainBegin.md): Bases: `Event`
- [`TrainEnd`](capymoa.ocl.evaluation.events.TrainEnd.md): Bases: `Event`
- [`TrainTaskBegin`](capymoa.ocl.evaluation.events.TrainTaskBegin.md): Bases: `Event`
- [`TrainTaskEnd`](capymoa.ocl.evaluation.events.TrainTaskEnd.md): Bases: `TrainTaskBegin`
- [`OCLMetrics`](capymoa.ocl.evaluation.OCLMetrics.md): Bases: `object`
- [`events`](capymoa.ocl.events.md): | `Dispatcher`   | Publish events to subscribed callbacks.                                          ...
- [`Dispatcher`](capymoa.ocl.events.Dispatcher.md): Bases: `object`
- [`Event`](capymoa.ocl.events.Event.md): Bases: `object`
- [`Handler`](capymoa.ocl.events.Handler.md): Bases: `ABC`
- [`strategy`](capymoa.ocl.strategy.md): Online Continual Learning (OCL) strategies.
- [`l2p`](capymoa.ocl.strategy.l2p.md): Learning to Prompt
- [`L2P`](capymoa.ocl.strategy.l2p.L2P.md): Bases: `BatchClassifier`, `Handler`
- [`L2PViT`](capymoa.ocl.strategy.l2p.L2PViT.md): Bases: `ABC`
- [`EWC`](capymoa.ocl.strategy.EWC.md): Bases: `BatchClassifier`, `Module`, `Handler`
- [`LWF`](capymoa.ocl.strategy.LWF.md): Bases: `BatchClassifier`, `Module`, `Handler`
- [`MAS`](capymoa.ocl.strategy.MAS.md): Bases: `BatchClassifier`, `Module`, `Handler`
- [`NCM`](capymoa.ocl.strategy.NCM.md): Bases: `BatchClassifier`
- [`RAR`](capymoa.ocl.strategy.RAR.md): Bases: `BatchClassifier`, `Handler`
- [`SI`](capymoa.ocl.strategy.SI.md): Bases: `BatchClassifier`, `Module`, `Handler`
- [`SLDA`](capymoa.ocl.strategy.SLDA.md): Bases: `BatchClassifier`
- [`ExperienceReplay`](capymoa.ocl.strategy.ExperienceReplay.md): Bases: `BatchClassifier`, `Handler`
- [`GDumb`](capymoa.ocl.strategy.GDumb.md): Bases: `BatchClassifier`, `Handler`
- [`RWalk`](capymoa.ocl.strategy.RWalk.md): Bases: `BatchClassifier`, `Module`, `Handler`
- [`util`](capymoa.ocl.util.md): | `data`             | Utilities for continual learning when using PyTorch datasets.   |
- [`data`](capymoa.ocl.util.data.md): Utilities for continual learning when using PyTorch datasets.
- [`functional`](capymoa.ocl.util.functional.md): A collection of functional utilities for OCL.
- [`ssl`](capymoa.ssl.md): Semi-supervised learning.
- [`OSNN`](capymoa.ssl.OSNN.md): Bases: `ClassifierSSL`
- [`SLEADE`](capymoa.ssl.SLEADE.md): Bases: `MOAClassifierSSL`
- [`automl`](capymoa.automl.md): Automatic machine learning.
- [`AutoClass`](capymoa.automl.AutoClass.md): Bases: `MOAClassifier`
- [`BanditClassifier`](capymoa.automl.BanditClassifier.md): Bases: `Classifier`
- [`EpsilonGreedy`](capymoa.automl.EpsilonGreedy.md): Bases: `object`
- [`SuccessiveHalvingClassifier`](capymoa.automl.SuccessiveHalvingClassifier.md): Bases: `Classifier`
- [`uncertainty`](capymoa.uncertainty.md): Uncertainty.
- [`MVE`](capymoa.uncertainty.MVE.md): Bases: `MOAPredictionIntervalLearner`
- [`AdaPI`](capymoa.uncertainty.AdaPI.md): Bases: `MOAPredictionIntervalLearner`
- [`feature`](capymoa.feature.md): Feature selection.
- [`FeatureImportanceClassifier`](capymoa.feature.FeatureImportanceClassifier.md): Bases: `Classifier`
- [`MOAFeatureImportanceClassifier`](capymoa.feature.MOAFeatureImportanceClassifier.md): Bases: `FeatureImportanceClassifier`, `MOAClassifier`
- [`base`](capymoa.base.md): Base classes for CapyMOA learners.
- [`AnomalyDetector`](capymoa.base.AnomalyDetector.md): Bases: `LearnerParamsMixin`, `ABC`
- [`Batch`](capymoa.base.Batch.md): Bases: `ABC`
- [`BatchClassifier`](capymoa.base.BatchClassifier.md): Bases: `Classifier`, `Batch`, `ABC`
- [`BatchRegressor`](capymoa.base.BatchRegressor.md): Bases: `Regressor`, `Batch`, `ABC`
- [`Classifier`](capymoa.base.Classifier.md): Bases: `LearnerParamsMixin`, `ABC`
- [`ClassifierSSL`](capymoa.base.ClassifierSSL.md): Bases: `Classifier`
- [`Clusterer`](capymoa.base.Clusterer.md): Bases: `LearnerParamsMixin`, `ABC`
- [`ClusteringResult`](capymoa.base.ClusteringResult.md): Bases: `object`
- [`LearnerParamsMixin`](capymoa.base.LearnerParamsMixin.md): Bases: `object`
- [`LearnerSpec`](capymoa.base.LearnerSpec.md): Bases: `TypedDict`
- [`MOAAnomalyDetector`](capymoa.base.MOAAnomalyDetector.md): Bases: `AnomalyDetector`
- [`MOAClassifier`](capymoa.base.MOAClassifier.md): Bases: `Classifier`
- [`MOAClassifierSSL`](capymoa.base.MOAClassifierSSL.md): Bases: `MOAClassifier`, `ClassifierSSL`
- [`MOAClusterer`](capymoa.base.MOAClusterer.md): Bases: `Clusterer`
- [`MOAPredictionIntervalLearner`](capymoa.base.MOAPredictionIntervalLearner.md): Bases: `MOARegressor`, `PredictionIntervalLearner`
- [`MOARegressor`](capymoa.base.MOARegressor.md): Bases: `Regressor`
- [`PredictionIntervalLearner`](capymoa.base.PredictionIntervalLearner.md): Bases: `Regressor`
- [`Regressor`](capymoa.base.Regressor.md): Bases: `LearnerParamsMixin`, `ABC`
- [`SKClassifier`](capymoa.base.SKClassifier.md): Bases: `Classifier`
- [`SKRegressor`](capymoa.base.SKRegressor.md): Bases: `Regressor`
- [`core`](capymoa.core.md): Shared utilities and core types used across CapyMOA.
- [`io`](capymoa.core.io.md): | `load_model`       | Load a model from a jpype pickle file.   |
- [`moa`](capymoa.core.moa.md): MOA (Massive Online Analysis) interoperability common module.
- [`splitcriteria`](capymoa.core.moa.splitcriteria.md): Module containing split criteria for decision trees.
- [`GiniSplitCriterion`](capymoa.core.moa.splitcriteria.GiniSplitCriterion.md): Bases: `SplitCriterion`
- [`InfoGainSplitCriterion`](capymoa.core.moa.splitcriteria.InfoGainSplitCriterion.md): Bases: `SplitCriterion`
- [`SplitCriterion`](capymoa.core.moa.splitcriteria.SplitCriterion.md): Bases: `object`
- [`VarianceReductionSplitCriterion`](capymoa.core.moa.splitcriteria.VarianceReductionSplitCriterion.md): Bases: `SplitCriterion`
- [`torch`](capymoa.core.torch.md): PyTorch utilities for CapyMOA.
- [`ann`](capymoa.core.torch.ann.md): Artificial Neural Networks for CapyMOA.
- [`LeNet5`](capymoa.core.torch.ann.LeNet5.md): Bases: `Module`
- [`Perceptron`](capymoa.core.torch.ann.Perceptron.md): Bases: `Module`
- [`Instance`](capymoa.core.Instance.md): Bases: `object`
- [`Label`](capymoa.core.Label.md): alias of `str`
- [`LabelIndex`](capymoa.core.LabelIndex.md): alias of `int`
- [`LabeledInstance`](capymoa.core.LabeledInstance.md): Bases: `Instance`
- [`RegressionInstance`](capymoa.core.RegressionInstance.md): Bases: `Instance`
- [`TargetValue`](capymoa.core.TargetValue.md): alias of `float64`
- [`datasets`](capymoa.datasets.md): CapyMOA comes with some datasets ‘out of the box’. Simply import the dataset
- [`KDD99`](capymoa.datasets.KDD99.md): Bases: `_DownloadableARFF`
- [`Airlines`](capymoa.datasets.Airlines.md): Bases: `_DownloadableARFF`
- [`Bike`](capymoa.datasets.Bike.md): Bases: `_DownloadableARFF`
- [`CovtFD`](capymoa.datasets.CovtFD.md): Bases: `_DownloadableARFF`
- [`Covtype`](capymoa.datasets.Covtype.md): Bases: `_DownloadableARFF`
- [`CovtypeNorm`](capymoa.datasets.CovtypeNorm.md): Bases: `_DownloadableARFF`
- [`CovtypeTiny`](capymoa.datasets.CovtypeTiny.md): Bases: `_DownloadableARFF`
- [`Electricity`](capymoa.datasets.Electricity.md): Bases: `_DownloadableARFF`
- [`ElectricityTiny`](capymoa.datasets.ElectricityTiny.md): Bases: `_DownloadableARFF`
- [`Fried`](capymoa.datasets.Fried.md): Bases: `_DownloadableARFF`
- [`FriedTiny`](capymoa.datasets.FriedTiny.md): Bases: `_DownloadableARFF`
- [`Hyper100k`](capymoa.datasets.Hyper100k.md): Bases: `_DownloadableARFF`
- [`Nomao`](capymoa.datasets.Nomao.md): Bases: `_DownloadableARFF`
- [`PokerHand`](capymoa.datasets.PokerHand.md): Bases: `_DownloadableARFF`
- [`RBFm_100k`](capymoa.datasets.RBFm_100k.md): Bases: `_DownloadableARFF`
- [`RTG_2abrupt`](capymoa.datasets.RTG_2abrupt.md): Bases: `_DownloadableARFF`
- [`Sensor`](capymoa.datasets.Sensor.md): Bases: `_DownloadableARFF`
- [`Spambase`](capymoa.datasets.Spambase.md): Bases: `_DownloadableARFF`
- [`evaluation`](capymoa.evaluation.md): Evaluation procedures and evaluators for CapyMOA learners.
- [`results`](capymoa.evaluation.results.md): | `PrequentialResults`   |    |
- [`PrequentialResults`](capymoa.evaluation.results.PrequentialResults.md): Bases: `object`
- [`AnomalyDetectionEvaluator`](capymoa.evaluation.AnomalyDetectionEvaluator.md): Bases: `object`
- [`ClassificationEvaluator`](capymoa.evaluation.ClassificationEvaluator.md): Bases: `object`
- [`ClassificationWindowedEvaluator`](capymoa.evaluation.ClassificationWindowedEvaluator.md): Bases: `ClassificationEvaluator`
- [`ClusteringEvaluator`](capymoa.evaluation.ClusteringEvaluator.md): Bases: `object`
- [`PredictionIntervalEvaluator`](capymoa.evaluation.PredictionIntervalEvaluator.md): Bases: `RegressionEvaluator`
- [`PredictionIntervalWindowedEvaluator`](capymoa.evaluation.PredictionIntervalWindowedEvaluator.md): Bases: `PredictionIntervalEvaluator`
- [`RegressionEvaluator`](capymoa.evaluation.RegressionEvaluator.md): Bases: `object`
- [`RegressionWindowedEvaluator`](capymoa.evaluation.RegressionWindowedEvaluator.md): Bases: `RegressionEvaluator`
- [`stream`](capymoa.stream.md): Data stream representations and related utilities.
- [`drift`](capymoa.stream.drift.md): Simulate concept drift in datastreams.
- [`AbruptDrift`](capymoa.stream.drift.AbruptDrift.md): Bases: `Drift`
- [`Concept`](capymoa.stream.drift.Concept.md): Bases: `object`
- [`Drift`](capymoa.stream.drift.Drift.md): Bases: `object`
- [`DriftStream`](capymoa.stream.drift.DriftStream.md): Bases: `Stream`
- [`GradualDrift`](capymoa.stream.drift.GradualDrift.md): Bases: `Drift`
- [`IndexedCycle`](capymoa.stream.drift.IndexedCycle.md): Bases: `object`
- [`RecurrentConceptDriftStream`](capymoa.stream.drift.RecurrentConceptDriftStream.md): Bases: `DriftStream`
- [`generator`](capymoa.stream.generator.md): Generate artificial data streams.
- [`AgrawalGenerator`](capymoa.stream.generator.AgrawalGenerator.md): Bases: `MOAStream`
- [`HyperPlaneClassification`](capymoa.stream.generator.HyperPlaneClassification.md): Bases: `MOAStream`
- [`HyperPlaneRegression`](capymoa.stream.generator.HyperPlaneRegression.md): Bases: `MOAStream`
- [`LEDGenerator`](capymoa.stream.generator.LEDGenerator.md): Bases: `MOAStream`
- [`LEDGeneratorDrift`](capymoa.stream.generator.LEDGeneratorDrift.md): Bases: `MOAStream`
- [`MixedGenerator`](capymoa.stream.generator.MixedGenerator.md): Bases: `MOAStream`
- [`RandomRBFGenerator`](capymoa.stream.generator.RandomRBFGenerator.md): Bases: `MOAStream`
- [`RandomRBFGeneratorDrift`](capymoa.stream.generator.RandomRBFGeneratorDrift.md): Bases: `MOAStream`
- [`RandomTreeGenerator`](capymoa.stream.generator.RandomTreeGenerator.md): Bases: `MOAStream`
- [`SEA`](capymoa.stream.generator.SEA.md): Bases: `MOAStream`
- [`STAGGERGenerator`](capymoa.stream.generator.STAGGERGenerator.md): Bases: `MOAStream`
- [`SineGenerator`](capymoa.stream.generator.SineGenerator.md): Bases: `MOAStream`
- [`WaveformGenerator`](capymoa.stream.generator.WaveformGenerator.md): Bases: `MOAStream`
- [`WaveformGeneratorDrift`](capymoa.stream.generator.WaveformGeneratorDrift.md): Bases: `MOAStream`
- [`preprocessing`](capymoa.stream.preprocessing.md): Data stream preprocessing and pipelines.
- [`BasePipeline`](capymoa.stream.preprocessing.BasePipeline.md): Bases: `PipelineElement`
- [`ClassifierPipeline`](capymoa.stream.preprocessing.ClassifierPipeline.md): Bases: `BasePipeline`, `Classifier`
- [`ClassifierPipelineElement`](capymoa.stream.preprocessing.ClassifierPipelineElement.md): Bases: `PipelineElement`
- [`DriftDetectorPipelineElement`](capymoa.stream.preprocessing.DriftDetectorPipelineElement.md): Bases: `PipelineElement`
- [`MOATransformer`](capymoa.stream.preprocessing.MOATransformer.md): Bases: `Transformer`
- [`PipelineElement`](capymoa.stream.preprocessing.PipelineElement.md): Bases: `Protocol`
- [`RandomSearchClassifierPE`](capymoa.stream.preprocessing.RandomSearchClassifierPE.md): Bases: `ClassifierPipelineElement`, `Classifier`
- [`RegressorPipeline`](capymoa.stream.preprocessing.RegressorPipeline.md): Bases: `BasePipeline`, `Regressor`
- [`RegressorPipelineElement`](capymoa.stream.preprocessing.RegressorPipelineElement.md): Bases: `PipelineElement`
- [`Transformer`](capymoa.stream.preprocessing.Transformer.md): Bases: `ABC`
- [`TransformerPipelineElement`](capymoa.stream.preprocessing.TransformerPipelineElement.md): Bases: `PipelineElement`
- [`ARFFStream`](capymoa.stream.ARFFStream.md): Bases: `MOAStream`[`_AnyInstance`]
- [`CSVStream`](capymoa.stream.CSVStream.md): Bases: `Stream`[`_AnyInstance`]
- [`MOAStream`](capymoa.stream.MOAStream.md): Bases: `Stream`[`_AnyInstance`]
- [`NumpyStream`](capymoa.stream.NumpyStream.md): Bases: `Stream`[`_AnyInstance`]
- [`Schema`](capymoa.stream.Schema.md): Bases: `object`
- [`Stream`](capymoa.stream.Stream.md): Bases: `ABC`, `Iterator`[`_AnyInstance`], [`Generic`](https://docs.python.org/3/library/typing.html#...
- [`TorchStream`](capymoa.stream.TorchStream.md): Bases: `Stream`
- [`env`](capymoa.env.md): Set and get capymoa environment variables.

## Optional

- [Top-level llms.txt](../../llms.txt): Complete documentation index.