PrepareWithoutTargetUnit
Prepare a dataset for a task that declares no target column.
The counterpart of PrepareAndSplitUnit for tasks whose
REQUIRES_TARGET is False, such as clustering. It validates the dataset
against the task, keeps the input columns and, unless told not to,
standardises them. Nothing is partitioned: such a task is fitted and scored
over every row, because there is nothing held out to evaluate against.
It publishes the features under their own key, features, a single
dataset, rather than reusing x: x is a dict of partitions, and the
name of a key is part of its contract. A graph validator compares names, so
a reused name with a different shape would let a wrong edge through.
n_labels is the task's answer to how many labels there are, which for a
task without a target is None -- the same value a regression task gives.
It is published so the unit that builds the model is fed the same way for
both kinds of task.
Parameters
- task_name : string, default=
TabularClassificationTask - Name of the task the dataset is prepared for.
- input_columns : array, default=
[] - Names of the columns used as model input.
- standardise : boolean, default=
True - Whether every numeric input column with any variance is centred and scaled before the model sees it. Models that measure distances are otherwise dominated by the column with the widest range.
Methods
execute(self, ctx: DashAI.back.units.context.ExecutionContext) -> None
PrepareWithoutTargetUnitDo the unit's work, reading from and writing to the context.
Parameters
- ctx : ExecutionContext
- The shared execution context.
get_credential(self, name: str)
ConfigObjectResolve a registered credential component by name.
Parameters
- name : str
- Credential component class name (e.g. "HuggingFaceCredential").
Returns
- BaseCredential
- An instance of the requested credential component.
get_schema(cls) -> dict
ConfigObjectGenerates the component related Json Schema.
Returns
- dict
- Dictionary representing the Json Schema of the component.
validate(self, ctx: DashAI.back.units.context.ExecutionContext) -> None
BaseUnitCheck preconditions without executing the unit.
Parameters
- ctx : ExecutionContext
- The shared execution context.
validate_and_transform(self, raw_data: dict) -> dict
ConfigObjectIt takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.
Parameters
- raw_data : dict
- A dictionary with the data provided by the user to initialize the model.
Returns
- dict
- A validated dictionary with the necessary objects.