Pipeline (Deedle) | Deedle

Pipeline Type

Namespace: Deedle.MicrosoftML
Assembly: Deedle.MicrosoftML.dll
Base Type: obj

Static helpers that extend the Frame concept with ML.NET pipeline operations. Open Deedle.MicrosoftML to use these alongside the standard Deedle API. ML.NET pipeline integration

Static members

Static member	Description
`Pipeline.applyTransformer transformer frame` Full Usage: `Pipeline.applyTransformer transformer frame` Parameters: transformer : `ITransformer` - A fitted ML.NET transformer. frame : `Frame<'R, string>` - The input Deedle frame. Returns: `Frame<int, string>` Type parameters: 'R (requires equality)	Apply an already-fitted ML.NET ITransformer to a Deedle Frame, returning the transformed data as a new `Frame<int, string>`. transformer : `ITransformer` A fitted ML.NET transformer. frame : `Frame<'R, string>` The input Deedle frame. Returns: `Frame<int, string>`
`Pipeline.fitEstimator estimator frame` Full Usage: `Pipeline.fitEstimator estimator frame` Parameters: estimator : `IEstimator<'T>` - An ML.NET estimator. frame : `Frame<'R, string>` - The training data as a Deedle frame. Returns: `'T` Type parameters: 'T, 'R (requires :> Microsoft.ML.ITransformer and equality)	Fit an ML.NET estimator on a Deedle Frame and return the fitted model without transforming. estimator : `IEstimator<'T>` An ML.NET estimator. frame : `Frame<'R, string>` The training data as a Deedle frame. Returns: `'T`
`Pipeline.fitTransform estimator frame` Full Usage: `Pipeline.fitTransform estimator frame` Parameters: estimator : `IEstimator<'T>` - An ML.NET estimator whose output transformer implements ITransformer. frame : `Frame<'R, string>` - The training data as a Deedle frame. Returns: `Frame<int, string>` Type parameters: 'T, 'R (requires :> Microsoft.ML.ITransformer and equality)	Fit an ML.NET estimator on a Deedle Frame and immediately apply the resulting transform, returning the output as a new `Frame<int, string>`. estimator : `IEstimator<'T>` An ML.NET estimator whose output transformer implements ITransformer. frame : `Frame<'R, string>` The training data as a Deedle frame. Returns: `Frame<int, string>`
`Pipeline.fitTransformOn estimator trainFrame testFrame` Full Usage: `Pipeline.fitTransformOn estimator trainFrame testFrame` Parameters: estimator : `IEstimator<'T>` - An ML.NET estimator. trainFrame : `Frame<'R, string>` - Training data. testFrame : `Frame<'S, string>` - Data to transform using the fitted model. Returns: `Frame<int, string>` Type parameters: 'T, 'R, 'S (requires :> Microsoft.ML.ITransformer and equality and equality)	Fit an estimator on a training frame, then apply it to a separate prediction/test frame and return the result. estimator : `IEstimator<'T>` An ML.NET estimator. trainFrame : `Frame<'R, string>` Training data. testFrame : `Frame<'S, string>` Data to transform using the fitted model. Returns: `Frame<int, string>`