Units

All registered Unit components in DashAI.

Name	Description
ApplyConverterUnit	Fit one converter on the scoped data and transform the same dataset.
ApplyDatasetSchemaUnit	Rename the dataset's columns and cast them to their declared types.
ApplySessionPreprocessingUnit	Publish the rows as the model was trained to see them.
BuildGlobalExplainerUnit	Instantiate a global explainer over an already trained model.
BuildLocalExplainerUnit	Instantiate a local explainer over an already trained model.
BuildManualInputUnit	Build the dataset to predict on from values the user typed in.
BuildModelUnit	Instantiate an untrained model bound to its data and metrics.
ComputeDatasetMetadataUnit	Fill in the metadata a dataset carries in its splits mapping.
EvaluateModelToArtifactUnit	Compute a trained model's metrics and publish them as data.
EvaluateModelUnit	Compute the final metrics of a trained model, once per split.
FitConverterUnit	Fit a converter on the dataset in the context and publish it fitted.
FitModelOverFoldsUnit	Fit a model once per fold, then once more on everything the folds used.
FitModelOverNestedFoldsUnit	Score every outer fold with a search that never saw it.
FitModelUnit	Train a model, running a hyperparameter search when there is one to run.
GenerateGlobalExplanationUnit	Explain the model over the whole dataset and pickle the result.
GenerateLocalExplanationUnit	Explain a selection of instances and pickle the result.
InferDatasetTypesUnit	Publish a type declaration for every column of the dataset.
LoadDatafileDatasetUnit	Parse a dataset out of a download that already completed.
LoadDatasetUnit	Load a dataset from disk into the execution context.
LoadRunModelUnit	Restore a run's trained model for an explanation.
LoadTrainedModelUnit	Rebuild a trained model from the run that produced it.
LoadTrainingDatasetUnit	Load the dataset a model was trained on, under a key of its own.
LoadUploadedDatasetUnit	Parse a file or URL into a dataset with the chosen reader.
PredictUnit	Predict with a trained model and decode the result into labels.
PrepareAndFoldUnit	Validate a dataset against a task and carve it into cross-validation folds.
PrepareAndSplitUnit	Validate a dataset against a task and split it once into three partitions.
PrepareExplanationDataUnit	Rebuild the exact train/test/val split the run was trained on.
RunExplorationUnit	Instantiate an explorer component and run it over the dataset.
SaveDatasetToPathUnit	Write the dataset to a destination given in the configuration.
SaveDatasetUnit	Write the dataset back to the path it was loaded from.
SaveExplorationUnit	Write an exploration result to disk and publish where it landed.
SaveModelUnit	Write a trained model under the runs directory, in its own subdirectory.
SavePredictionUnit	Write the predicted column next to the data it was predicted from.
TransformDatasetUnit	Apply an already fitted converter to the dataset in the context.