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# Create ML Components

Create more customizable machine learning models in your app.

## Overview

Create ML Components is a fundamental technology that exposes the underpinnings of monolithic tasks. You’re in full control and can create custom pipelines for greater flexibility.

![A flowchart that depicts a task represented as 4 component rectangles. The flow begins in the bottom left rectangle which has a camera icon to represent an input image and a label that reads Component 0. This rectangle has two flow arrows — one points up to the single rectangle above the other three rectangles. This top rectangle has a wand and four stars icon that represents an enhancement to the image and a label that reads Component 1. The second flow arrow points to the bottom center rectangle which has a screen within a screen scaling icon that represents the resizing of the image and a label that reads Component 2. Next, the single top rectangle has a flow arrow that points down to the bottom right rectangle which has a photo icon that represents the finished image and a label that reads Component n. A series of three dots connects this rectangle to the center rectangle in the bottom row.](images/com.apple.createmlcomponents/create-ml-task@2x.png)

Use components to configure your machine learning tasks with a detailed level of granularity. Choose a specific classifier for images, video, or tabular data.

## Topics

### Image components

[Augmenting images to expand your training data](/documentation/CreateMLComponents/augmenting-images-to-expand-your-training-data)

Improve your model by using transformed versions of your training images.

[Creating a multi-label image classifier](/documentation/CreateMLComponents/creating-a-multi-label-image-classifier)

Train a machine learning model to assign multiple labels to an image.

[`ImageReader`](/documentation/CreateMLComponents/ImageReader)

An image file reader.

[`ImageFeatureExtractor`](/documentation/CreateMLComponents/ImageFeatureExtractor)

A transformer that takes an image and outputs image features.

[`ImageCropper`](/documentation/CreateMLComponents/ImageCropper)

An image crop transformer.

[`ImageScaler`](/documentation/CreateMLComponents/ImageScaler)

An image scaling transformer.

[`ImageFeaturePrint`](/documentation/CreateMLComponents/ImageFeaturePrint)

ImageFeaturePrint image feature extractor.

[`ImageBlur`](/documentation/CreateMLComponents/ImageBlur)

An image blurring transformer.

[`ImageColorTransformer`](/documentation/CreateMLComponents/ImageColorTransformer)

An image color transformer.

[`ImageExposureAdjuster`](/documentation/CreateMLComponents/ImageExposureAdjuster)

An image exposure adjusting transformer.

[`ImageFlipper`](/documentation/CreateMLComponents/ImageFlipper)

An image flipper transformer.

[`ImageRotator`](/documentation/CreateMLComponents/ImageRotator)

An image rotating transformer.

[`RandomImageNoiseGenerator`](/documentation/CreateMLComponents/RandomImageNoiseGenerator)

A transformer that adds random noise to an image.

[`MLModelImageFeatureExtractor`](/documentation/CreateMLComponents/MLModelImageFeatureExtractor)

An image feature extractor provided by an MLModel.

### Pose components

[Counting human body action repetitions in a live video feed](/documentation/CreateMLComponents/counting-human-body-action-repetitions-in-a-live-video-feed)

Use Create ML Components to analyze a series of video frames and count a person’s
repetitive or periodic body movements.

[`Pose`](/documentation/CreateMLComponents/Pose)

A pose that contains joint keypoints from a person, a hand, or a combination.

[`JointKey`](/documentation/CreateMLComponents/JointKey)

A key that uniquely identifies a joint.

[`JointPoint`](/documentation/CreateMLComponents/JointPoint)

A joint in a pose that contains a location and scoring information.

[`PoseSelector`](/documentation/CreateMLComponents/PoseSelector)

A transformer that selects one pose from an array of poses.

[`PoseSelectionStrategy`](/documentation/CreateMLComponents/PoseSelectionStrategy)

Pose selection strategy.

[`JointsSelector`](/documentation/CreateMLComponents/JointsSelector)

Joints selector from a pose.

[`HumanBodyPoseExtractor`](/documentation/CreateMLComponents/HumanBodyPoseExtractor)

The human body pose image feature extractor.

[`HumanHandPoseExtractor`](/documentation/CreateMLComponents/HumanHandPoseExtractor)

The human hand pose image feature extractor.

[`HumanBodyActionCounter`](/documentation/CreateMLComponents/HumanBodyActionCounter)

A human body action repetition counting transformer that takes window of human body poses and produces cumulative human body action repetition counts.

[`HumanBodyActionPeriodPredictor`](/documentation/CreateMLComponents/HumanBodyActionPeriodPredictor)

A human body action period predictor transformer that takes window of poses and produces a window of predictions.

### Audio components

[`AudioReader`](/documentation/CreateMLComponents/AudioReader)

An audio file reader.

[`AudioFeaturePrint`](/documentation/CreateMLComponents/AudioFeaturePrint)

A stream transformer that extracts audio features from audio buffers.

[`AudioConvertingTransformer`](/documentation/CreateMLComponents/AudioConvertingTransformer)

A transformer for audio conversion.

### Time-based components

[Creating a time-series classifier](/documentation/CreateMLComponents/creating-a-time-series-classifier)

Train a machine learning model to predict the class label of time-series signals.

[Creating a time-series forecaster](/documentation/CreateMLComponents/creating-a-time-series-forecaster)

Forecast future data points by training a machine learning model using historical data.

[`DateFeatures`](/documentation/CreateMLComponents/DateFeatures)

A set of date and time features.

[`DateFeatureExtractor`](/documentation/CreateMLComponents/DateFeatureExtractor)

A time and date feature extractor.

[`LinearTimeSeriesForecaster`](/documentation/CreateMLComponents/LinearTimeSeriesForecaster)

A time-series forecasting estimator.

[`LinearTimeSeriesForecasterConfiguration`](/documentation/CreateMLComponents/LinearTimeSeriesForecasterConfiguration)

The configuration for a linear time-series forecaster.

[`TimeSeriesForecasterBatches`](/documentation/CreateMLComponents/TimeSeriesForecasterBatches)

A sequence of forecaster batches on a time series shaped array.

[`TimeSeriesForecasterAnnotatedWindows`](/documentation/CreateMLComponents/TimeSeriesForecasterAnnotatedWindows)

A sequence of forecasting windows on a time series shaped array.

[`TemporalFeature`](/documentation/CreateMLComponents/TemporalFeature)

A temporal feature contains a segment identifier and a feature value.

[`TemporalSequence`](/documentation/CreateMLComponents/TemporalSequence)

Async sequence for temporal features.

[`TemporalSegmentIdentifier`](/documentation/CreateMLComponents/TemporalSegmentIdentifier)

Uniquely identifiers a segment of a temporal sequence.

[`SlidingWindows`](/documentation/CreateMLComponents/SlidingWindows)

A sequence of windows on a time series shaped array.

[`SlidingWindowTransformer`](/documentation/CreateMLComponents/SlidingWindowTransformer)

A temporal transformer that groups input elements.

[`Downsampler`](/documentation/CreateMLComponents/Downsampler)

A temporal transformer that down samples the input stream.

[`VideoReader`](/documentation/CreateMLComponents/VideoReader)

A video file reader.

[`TemporalFileSegment`](/documentation/CreateMLComponents/TemporalFileSegment)

A URL and a time range identifying a specific segment of a time-based (temporal) file.

[`AnyTemporalIterator`](/documentation/CreateMLComponents/AnyTemporalIterator)

A type-erased async iterator.

[`AnyTemporalSequence`](/documentation/CreateMLComponents/AnyTemporalSequence)

A type-erased temporal sequence.

[`PreprocessedFeatureSequence`](/documentation/CreateMLComponents/PreprocessedFeatureSequence)

An asynchronous sequence of eagerly stored temporal features.

### Object detection components

[`DetectedObject`](/documentation/CreateMLComponents/DetectedObject)

An item in a detection result.

[`ObjectDetectionAnnotation`](/documentation/CreateMLComponents/ObjectDetectionAnnotation)

An object detection annotation.

[`ObjectDetectionMetrics`](/documentation/CreateMLComponents/ObjectDetectionMetrics)

Metrics for object detection model.

### Tabular components

[`TabularTransformer`](/documentation/CreateMLComponents/TabularTransformer)

A tabular transformer that transforms a data frame.

[`TabularEstimator`](/documentation/CreateMLComponents/TabularEstimator)

A tabular estimator that creates a transformer by fitting to a data set in a data frame.

[`SupervisedTabularEstimator`](/documentation/CreateMLComponents/SupervisedTabularEstimator)

A tabular estimator that creates a transformer by fitting to a data set in a data frame.

[`ColumnSelector`](/documentation/CreateMLComponents/ColumnSelector)

An operation that applies an estimator to a selection of columns.

[`ColumnSelectorTransformer`](/documentation/CreateMLComponents/ColumnSelectorTransformer)

A transformer that applies a base transformer to specific columns in a data frame.

[`ColumnSelection`](/documentation/CreateMLComponents/ColumnSelection)

A selection of columns from a data frame.

[`ColumnConcatenator`](/documentation/CreateMLComponents/ColumnConcatenator)

A transformer that concatenates every numerical column in a dataframe into to a shaped array for each row.

[`PreprocessingSupervisedTabularEstimator`](/documentation/CreateMLComponents/PreprocessingSupervisedTabularEstimator)

A supervised tabular estimator that composes a preprocessing transformer and a supervised tabular estimator.

[`PreprocessingTabularEstimator`](/documentation/CreateMLComponents/PreprocessingTabularEstimator)

An estimator that composes a preprocessing transformer and an estimator.

[`PreprocessingUpdatableSupervisedTabularEstimator`](/documentation/CreateMLComponents/PreprocessingUpdatableSupervisedTabularEstimator)

An updatable supervised estimator that composes a preprocessing transformer and an updatable supervised estimator.

[`PreprocessingUpdatableTabularEstimator`](/documentation/CreateMLComponents/PreprocessingUpdatableTabularEstimator)

An updatable estimator that composes a preprocessing transformer and an updatable estimator.

### Protocols

[`Transformer`](/documentation/CreateMLComponents/Transformer)

A transformer that takes an input and produces an output.

[`TemporalTransformer`](/documentation/CreateMLComponents/TemporalTransformer)

A transformer that takes an asynchronous input sequence of temporal features and produces an asynchronous output  sequence.

[`RandomTransformer`](/documentation/CreateMLComponents/RandomTransformer)

A transformer that takes an input and a random number generator and produces a randomized output.

[`Estimator`](/documentation/CreateMLComponents/Estimator)

An estimator that creates a transformer by fitting to a data set.

[`TemporalEstimator`](/documentation/CreateMLComponents/TemporalEstimator)

An estimator that creates a transformer by fitting to a sequence of temporal features.

[`SupervisedEstimator`](/documentation/CreateMLComponents/SupervisedEstimator)

An estimator that creates a transformer by fitting to a data set.

[`SupervisedTemporalEstimator`](/documentation/CreateMLComponents/SupervisedTemporalEstimator)

An estimator that creates a transformer by fitting to a sequence of annotated temporal features.

[`UpdatableEstimator`](/documentation/CreateMLComponents/UpdatableEstimator)

An estimator that can be incrementally updated.

[`UpdatableSupervisedEstimator`](/documentation/CreateMLComponents/UpdatableSupervisedEstimator)

A supervised estimator that can be incrementally updated.

[`UpdatableSupervisedTemporalEstimator`](/documentation/CreateMLComponents/UpdatableSupervisedTemporalEstimator)

A supervised temporal estimator that can be incrementally updated.

[`UpdatableSupervisedTabularEstimator`](/documentation/CreateMLComponents/UpdatableSupervisedTabularEstimator)

A supervised tabular estimator that can be incrementally updated.

[`UpdatableTemporalEstimator`](/documentation/CreateMLComponents/UpdatableTemporalEstimator)

A temporal estimator that can be incrementally updated.

[`UpdatableTabularEstimator`](/documentation/CreateMLComponents/UpdatableTabularEstimator)

A tabular estimator that can be incrementally updated.

### Core ML adaptors

[`MLModelTransformerAdaptor`](/documentation/CreateMLComponents/MLModelTransformerAdaptor)

A transformer that uses a Core ML model.

[`MLModelClassifierAdaptor`](/documentation/CreateMLComponents/MLModelClassifierAdaptor)

A transformer that uses a Core ML model as a classifier.

[`MLModelRegressorAdaptor`](/documentation/CreateMLComponents/MLModelRegressorAdaptor)

A transformer that uses a Core ML model as a regressor.

[`ModelMetadata`](/documentation/CreateMLComponents/ModelMetadata)

User info keys that specify useful information about a model.

### Annotations

[`AnnotatedFiles`](/documentation/CreateMLComponents/AnnotatedFiles)

An annotated files collection.

[`AnnotatedBatch`](/documentation/CreateMLComponents/AnnotatedBatch)

A batch of annotated examples for fitting a supervised estimator.

[`AnnotatedFeature`](/documentation/CreateMLComponents/AnnotatedFeature)

An annotated example for fitting a supervised estimator.

[`AnnotatedFeatureProvider`](/documentation/CreateMLComponents/AnnotatedFeatureProvider)

An adaptor that converts a regular estimator to a tabular estimator by selecting features and annotations from columns.

[`AnnotatedPrediction`](/documentation/CreateMLComponents/AnnotatedPrediction)

An annotated prediction.

[`DataFrameTemporalAnnotationParameters`](/documentation/CreateMLComponents/DataFrameTemporalAnnotationParameters)

Annotation parameters for the dataframe containing temporal annotations.

### Augmentations

[`ApplyEachRandomly`](/documentation/CreateMLComponents/ApplyEachRandomly)

Applies each transformer randomly given a probability.

[`ApplyRandomly`](/documentation/CreateMLComponents/ApplyRandomly)

Randomly applies the transformer with the given probability.

[`AugmentationBuilder`](/documentation/CreateMLComponents/AugmentationBuilder)

A series of augmentations.

[`AugmentationSequence`](/documentation/CreateMLComponents/AugmentationSequence)

An async sequence of augmented elements.

[`Augmenter`](/documentation/CreateMLComponents/Augmenter)

An augmenter.

[`ChooseRandomly`](/documentation/CreateMLComponents/ChooseRandomly)

Apply single transformation randomly chosen from a list of transformers.

[`RandomImageCropper`](/documentation/CreateMLComponents/RandomImageCropper)

Crops an image at a random location.

[`ShuffleRandomly`](/documentation/CreateMLComponents/ShuffleRandomly)

Apply transformations in a random order.

[`UniformRandomFloatingPointParameter`](/documentation/CreateMLComponents/UniformRandomFloatingPointParameter)

Applies the transformer with a randomly generated input parameter.

[`UniformRandomIntegerParameter`](/documentation/CreateMLComponents/UniformRandomIntegerParameter)

Applies the transformer with a randomly generated input parameter.

[`UpsampledAugmentationSequence`](/documentation/CreateMLComponents/UpsampledAugmentationSequence)

An async sequence of augmented elements.

### Event handling

[`Event`](/documentation/CreateMLComponents/Event)

Maintains the status of the pipeline.

[`EventHandler`](/documentation/CreateMLComponents/EventHandler)

A closure to handle processing events.

[`MetricsKey`](/documentation/CreateMLComponents/MetricsKey)

A key that uniquely identifies a metric.

### Scalers

[`StandardScaler`](/documentation/CreateMLComponents/StandardScaler)

An estimator that standardizes the input by removing the mean and scaling to unit variance.

[`MaxAbsScaler`](/documentation/CreateMLComponents/MaxAbsScaler)

An estimator that scales the input values so that the maximum absolute value is 1.0.

[`MinMaxScaler`](/documentation/CreateMLComponents/MinMaxScaler)

An estimator that scales the input values so that they all lie in a closed range.

[`NormalizationScaler`](/documentation/CreateMLComponents/NormalizationScaler)

An estimator that normalizes the input values using a normalization strategy.

[`RobustScaler`](/documentation/CreateMLComponents/RobustScaler)

An estimator that scales the input using statistics that are robust to outliers.

### Preprocessors

[`LinearTransformer`](/documentation/CreateMLComponents/LinearTransformer)

A transformer that runs an input through a scale and offset.

[`ImputeTransformer`](/documentation/CreateMLComponents/ImputeTransformer)

A transformer that replaces missing values with a pre-defined value.

[`OneHotEncoder`](/documentation/CreateMLComponents/OneHotEncoder)

An estimator that encodes categorical values to an integer array.

[`OrdinalEncoder`](/documentation/CreateMLComponents/OrdinalEncoder)

An ordinal encoder estimator encodes categorical values to ordinal integer values.

[`NumericImputer`](/documentation/CreateMLComponents/NumericImputer)

An estimator that replaces missing values in the numeric input.

[`Reshaper`](/documentation/CreateMLComponents/Reshaper)

A transformer that reshapes a shaped array.

[`CategoricalImputer`](/documentation/CreateMLComponents/CategoricalImputer)

An estimator that replaces missing values in the categorical input.

[`OptionalUnwrapper`](/documentation/CreateMLComponents/OptionalUnwrapper)

A transformer that unwraps optional elements and throws when encountering missing values.

### Regressors

[`Regressor`](/documentation/CreateMLComponents/Regressor)

A transformer that predicts a float value.

[`LinearRegressor`](/documentation/CreateMLComponents/LinearRegressor)

A linear regressor.

[`LinearRegressorModel`](/documentation/CreateMLComponents/LinearRegressorModel)

A trained linear regressor model.

[`MultivariateLinearRegressor`](/documentation/CreateMLComponents/MultivariateLinearRegressor)

A multivariate linear regressor.

[`MultivariateLinearRegressorConfiguration`](/documentation/CreateMLComponents/MultivariateLinearRegressorConfiguration)

A linear regressor configuration.

[`MultivariateLinearRegressor.Model`](/documentation/CreateMLComponents/MultivariateLinearRegressor/Model)

A trained multivariate linear regressor model.

[`FullyConnectedNetworkRegressor`](/documentation/CreateMLComponents/FullyConnectedNetworkRegressor)

A regressor that uses a fully connected network.

[`FullyConnectedNetworkRegressorModel`](/documentation/CreateMLComponents/FullyConnectedNetworkRegressorModel)

A regressor model that uses a fully connected network.

[`BoostedTreeRegressor`](/documentation/CreateMLComponents/BoostedTreeRegressor)

A gradient boosted decision tree regressor.

[`TreeRegressorModel`](/documentation/CreateMLComponents/TreeRegressorModel)

A trained tree regressor model.

[`OptimizationStrategy`](/documentation/CreateMLComponents/OptimizationStrategy)

A linear optimization strategy.

### Serializers

[`EstimatorDecoder`](/documentation/CreateMLComponents/EstimatorDecoder)

A type that can decode values from a model representation.

[`EstimatorEncoder`](/documentation/CreateMLComponents/EstimatorEncoder)

A type that can encode values into a model representation.

### Classifiers

[`Classifier`](/documentation/CreateMLComponents/Classifier)

An estimator that predicts classification probabilities.

[`LogisticRegressionClassifier`](/documentation/CreateMLComponents/LogisticRegressionClassifier)

A logistic regression classifier.

[`LogisticRegressionClassifierModel`](/documentation/CreateMLComponents/LogisticRegressionClassifierModel)

A trained logistic regression classifier model.

[`BoostedTreeClassifier`](/documentation/CreateMLComponents/BoostedTreeClassifier)

A gradient boosted decision tree classifier.

[`BoostedTreeConfiguration`](/documentation/CreateMLComponents/BoostedTreeConfiguration)

A boosted tree configuration.

[`FullyConnectedNetworkClassifier`](/documentation/CreateMLComponents/FullyConnectedNetworkClassifier)

A classifier that uses a fully connected network.

[`FullyConnectedNetworkClassifierModel`](/documentation/CreateMLComponents/FullyConnectedNetworkClassifierModel)

A classifier model that uses a fully connected network.

[`FullyConnectedNetworkMultiLabelClassifier`](/documentation/CreateMLComponents/FullyConnectedNetworkMultiLabelClassifier)

A classifier that uses a multi-label fully-connected network.

[`FullyConnectedNetworkMultiLabelClassifierModel`](/documentation/CreateMLComponents/FullyConnectedNetworkMultiLabelClassifierModel)

A multi-label classifier model that uses a fully-connected network.

[`FullyConnectedNetworkConfiguration`](/documentation/CreateMLComponents/FullyConnectedNetworkConfiguration)

A fully connected network configuration.

[`TreeClassifierModel`](/documentation/CreateMLComponents/TreeClassifierModel)

A trained tree classifier model.

[`TimeSeriesClassifier`](/documentation/CreateMLComponents/TimeSeriesClassifier)

[`TimeSeriesClassifierConfiguration`](/documentation/CreateMLComponents/TimeSeriesClassifierConfiguration)

The configuration for a time-series classifier.

### Metrics

[`Classification`](/documentation/CreateMLComponents/Classification)

An item in a classification result.

[`ClassificationDistribution`](/documentation/CreateMLComponents/ClassificationDistribution)

A classification distribution that contains a probability for each classification label.

[`ClassificationMetrics`](/documentation/CreateMLComponents/ClassificationMetrics)

Classification metrics.

[`MultiLabelClassificationMetrics`](/documentation/CreateMLComponents/MultiLabelClassificationMetrics)

Multi-label classification metrics.

[`rootMeanSquaredError(_:)`](/documentation/CreateMLComponents/rootMeanSquaredError(_:))

Computes the root mean squared error between predicted and ground truth values.

[`rootMeanSquaredError(_:_:)`](/documentation/CreateMLComponents/rootMeanSquaredError(_:_:))

Computes the root mean squared error between predicted and ground truth values.

[`maximumAbsoluteError(_:)`](/documentation/CreateMLComponents/maximumAbsoluteError(_:))

Computes the maximum absolute error between predicted and ground truth values.

[`maximumAbsoluteError(_:_:)`](/documentation/CreateMLComponents/maximumAbsoluteError(_:_:))

Computes the maximum absolute error between predicted and ground truth values.

[`meanAbsoluteError(_:)`](/documentation/CreateMLComponents/meanAbsoluteError(_:))

Computes the mean absolute error between predicted and ground truth values.

[`meanAbsoluteError(_:_:)`](/documentation/CreateMLComponents/meanAbsoluteError(_:_:))

Computes the mean absolute error between predicted and ground truth values.

[`meanAbsolutePercentageError(_:)`](/documentation/CreateMLComponents/meanAbsolutePercentageError(_:))

Computes the mean absolute percentage error between predicted and ground truth values.

[`meanSquaredError(_:)`](/documentation/CreateMLComponents/meanSquaredError(_:))

Computes the root mean squared error between predicted and ground truth values.

[`meanSquaredError(_:_:)`](/documentation/CreateMLComponents/meanSquaredError(_:_:))

Computes the mean squared error between predicted and ground truth values.

### Transformer adaptors

[`TransformerToEstimatorAdaptor`](/documentation/CreateMLComponents/TransformerToEstimatorAdaptor)

An estimator that always returns a predefined transformer.

[`TransformerToTemporalAdaptor`](/documentation/CreateMLComponents/TransformerToTemporalAdaptor)

A temporal transformer that applies a regular transformer to each value of a temporal sequence.

[`TransformerToUpdatableEstimatorAdaptor`](/documentation/CreateMLComponents/TransformerToUpdatableEstimatorAdaptor)

An updatable estimator that always returns a predefined transformer.

### Updatable adaptors

[`UpdatableEstimatorToTemporalAdaptor`](/documentation/CreateMLComponents/UpdatableEstimatorToTemporalAdaptor)

An updatable temporal estimator wrapping an updatable estimator.

[`UpdatableEstimatorToSupervisedAdaptor`](/documentation/CreateMLComponents/UpdatableEstimatorToSupervisedAdaptor)

An adaptor that exposes an updatable estimator as an updatable supervised estimator.

[`UpdatableSupervisedEstimatorToTemporalAdaptor`](/documentation/CreateMLComponents/UpdatableSupervisedEstimatorToTemporalAdaptor)

An updatable supervised temporal estimator wrapping an updatable supervised estimator.

[`UpdatableTemporalEstimatorToSupervisedAdaptor`](/documentation/CreateMLComponents/UpdatableTemporalEstimatorToSupervisedAdaptor)

An adaptor that exposes an updatable temporal estimator as an updatable supervised temporal estimator.

### Estimator adaptors

[`EstimatorToSupervisedAdaptor`](/documentation/CreateMLComponents/EstimatorToSupervisedAdaptor)

An adaptor that exposes an estimator as a supervised estimator.

[`EstimatorToTemporalAdaptor`](/documentation/CreateMLComponents/EstimatorToTemporalAdaptor)

A temporal estimator wrapping an estimator.

[`SupervisedEstimatorToTemporalAdaptor`](/documentation/CreateMLComponents/SupervisedEstimatorToTemporalAdaptor)

A supervised temporal estimator wrapping a supervised estimator.

### Tabular adaptors

[`TabularEstimatorToSupervisedAdaptor`](/documentation/CreateMLComponents/TabularEstimatorToSupervisedAdaptor)

An adaptor that exposes a tabular estimator as a tabular supervised estimator.

[`TabularTransformerToEstimatorAdaptor`](/documentation/CreateMLComponents/TabularTransformerToEstimatorAdaptor)

A tabular estimator that always returns a predefined tabular transformer.

[`TabularTransformerToUpdatableEstimatorAdaptor`](/documentation/CreateMLComponents/TabularTransformerToUpdatableEstimatorAdaptor)

An updatable tabular estimator that always returns a predefined transformer.

[`UpdatableTabularEstimatorToSupervisedAdaptor`](/documentation/CreateMLComponents/UpdatableTabularEstimatorToSupervisedAdaptor)

An adaptor that exposes an updatable tabular estimator as an updatable supervised tabular estimator.

### Temporal adaptors

[`TemporalAdaptor`](/documentation/CreateMLComponents/TemporalAdaptor)

A temporal transformer that applies a regular transformer to each value of a temporal sequence.

[`TemporalTransformerToEstimatorAdaptor`](/documentation/CreateMLComponents/TemporalTransformerToEstimatorAdaptor)

A temporal estimator that always returns a predefined temporal transformer.

[`TemporalEstimatorToSupervisedAdaptor`](/documentation/CreateMLComponents/TemporalEstimatorToSupervisedAdaptor)

An adaptor that exposes a temporal estimator as a supervised temporal estimator.

[`TemporalTransformerToUpdatableEstimatorAdaptor`](/documentation/CreateMLComponents/TemporalTransformerToUpdatableEstimatorAdaptor)

A temporal estimator that always returns a predefined temporal transformer.

### Composition with preprocessing

[`PreprocessingEstimator`](/documentation/CreateMLComponents/PreprocessingEstimator)

An estimator that composes a preprocessing transformer and an estimator.

[`PreprocessingTemporalEstimator`](/documentation/CreateMLComponents/PreprocessingTemporalEstimator)

A temporal estimator that composes a preprocessing transformer and a temporal estimator.

[`PreprocessingSupervisedEstimator`](/documentation/CreateMLComponents/PreprocessingSupervisedEstimator)

A supervised estimator that composes a preprocessing transformer and a supervised estimator.

[`PreprocessingSupervisedTemporalEstimator`](/documentation/CreateMLComponents/PreprocessingSupervisedTemporalEstimator)

A supervised temporal estimator that composes a preprocessing transformer and a supervised temporal estimator.

[`PreprocessingUpdatableEstimator`](/documentation/CreateMLComponents/PreprocessingUpdatableEstimator)

An updatable estimator that composes a preprocessing transformer and an updatable estimator.

[`PreprocessingUpdatableTemporalEstimator`](/documentation/CreateMLComponents/PreprocessingUpdatableTemporalEstimator)

An updatable temporal estimator that composes a preprocessing transformer and an updatable temporal estimator.

[`PreprocessingUpdatableSupervisedEstimator`](/documentation/CreateMLComponents/PreprocessingUpdatableSupervisedEstimator)

An updatable supervised estimator that composes a preprocessing transformer and an updatable supervised estimator.

[`PreprocessingUpdatableSupervisedTemporalEstimator`](/documentation/CreateMLComponents/PreprocessingUpdatableSupervisedTemporalEstimator)

An updatable supervised temporal estimator that composes a preprocessing transformer and an updatable supervised temporal estimator.

### Composition

[`ComposedTransformer`](/documentation/CreateMLComponents/ComposedTransformer)

A transformer that composes two transformers by applying them one after the other.

[`ComposedTemporalTransformer`](/documentation/CreateMLComponents/ComposedTemporalTransformer)

A temporal transformer that composes two temporal transformers by applying them one after the other.

[`ComposedTabularTransformer`](/documentation/CreateMLComponents/ComposedTabularTransformer)

A transformer that composes two tabular transformers by applying them one after the other.

### Errors

[`AudioPreprocessingError`](/documentation/CreateMLComponents/AudioPreprocessingError)

Audio preprocessing errors.

[`AudioReaderError`](/documentation/CreateMLComponents/AudioReaderError)

Audio reader errors.

[`CompatibilityError`](/documentation/CreateMLComponents/CompatibilityError)

A compatibility error.

[`ConcatenationError`](/documentation/CreateMLComponents/ConcatenationError)

Errors thrown when concatenating numeric values.

[`DatasetError`](/documentation/CreateMLComponents/DatasetError)

Dataset processing errors.

[`EstimatorEncodingError`](/documentation/CreateMLComponents/EstimatorEncodingError)

An estimator encoding error.

[`ModelCompatibilityError`](/documentation/CreateMLComponents/ModelCompatibilityError)

Errors related to CoreML model compatibility.

[`ModelUpdateError`](/documentation/CreateMLComponents/ModelUpdateError)

An updatable model error.

[`OptimizationError`](/documentation/CreateMLComponents/OptimizationError)

An optimization error.

[`PipelineDataError`](/documentation/CreateMLComponents/PipelineDataError)

Errors related to pipeline data affinity problems.

[`SerializationError`](/documentation/CreateMLComponents/SerializationError)

A serialization error.

[`TabularPipelineDataError`](/documentation/CreateMLComponents/TabularPipelineDataError)

Errors related to tabular pipeline data affinity problems.

[`VideoReaderError`](/documentation/CreateMLComponents/VideoReaderError)

Video loader errors.


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