Operation

class fedot.core.operations.operation.Operation(operation_type, log=None, **kwargs)

Bases: object

Base class for operations in nodes. Operations could be machine learning (or statistical) models or data operations

Parameters

  • operation_type (str) – name of the operation

  • log (Optional[fedot.core.log.Log]) – Log object to record messages

description(operation_params)
Parameters

operation_params (dict) –

Return type

str

property acceptable_task_types
property metadata
fit(params, data, is_fit_pipeline_stage=True)

This method is used for defining and running of the evaluation strategy to train the operation with the data provided

Parameters

  • params (Union[str, dict, None]) – hyperparameters for operation

  • data (fedot.core.data.data.InputData) – data used for operation training

  • is_fit_pipeline_stage (bool) – is this fit or predict stage for pipeline

Returns

tuple of trained operation and prediction on train data

predict(fitted_operation, data, is_fit_pipeline_stage, params=None, output_mode='default')

This method is used for defining and running of the evaluation strategy to predict with the data provided

Parameters

  • fitted_operation – trained operation object

  • data (fedot.core.data.data.InputData) – data used for prediction

  • is_fit_pipeline_stage (bool) – is this fit or predict stage for pipeline

  • params (Union[str, dict, None]) – hyperparameters for operation

  • output_mode (str) – string with information about output of operation,

for example, is the operation predict probabilities or class labels

abstract static assign_tabular_column_types(output_data, output_mode)

Assign types for columns based on task and output_mode (for classification) For example, pipeline for solving time series forecasting task contains lagged and ridge operations. ts_type -> lagged -> tabular type. So, there is a need to assign column types to new data

Parameters
Return type

fedot.core.data.data.OutputData

Model

class fedot.core.operations.model.Model(operation_type, log=None)

Bases: fedot.core.operations.operation.Operation

Class with fit/predict methods defining the evaluation strategy for the task

Parameters

  • operation_type (str) – name of the model

  • log (Optional[fedot.core.log.Log]) – Log object to record messages

static assign_tabular_column_types(output_data, output_mode)

Assign types for tabular data obtained from model predictions. By default, all types of model predictions for tabular data can be clearly defined

Parameters
Return type

fedot.core.data.data.OutputData

Data operation

class fedot.core.operations.data_operation.DataOperation(operation_type, log=None)

Bases: fedot.core.operations.operation.Operation

Class with fit/predict methods defining the evaluation strategy for the task

Parameters

  • operation_type (str) – name of the data operation

  • log (Optional[fedot.core.log.Log]) – Log object to record messages

property metadata
static assign_tabular_column_types(output_data, output_mode)

Assign new column types if it necessary. By default, all data operations must define column types at lower levels (EvalStrategies and Implementations). In some cases the previously defined data types are passed.

Parameters
Return type

fedot.core.data.data.OutputData