lib.sedna.algorithms.seen_task_learning.task_allocation.task_allocation

Mining tasks of inference sample based on task attribute extractor

param samples ： infer sample:

param see sedna.datasources.BaseDataSource for more detail.:

returns:

allocations

rtype:

tasks that assigned to each sample

Module Contents

Classes

TaskAllocationBySVC

Corresponding to TaskDefinitionBySVC

TaskAllocationByDataAttr

Corresponding to TaskDefinitionByDataAttr

TaskAllocationDefault

Task allocation specifically for unstructured data
class lib.sedna.algorithms.seen_task_learning.task_allocation.task_allocation.TaskAllocationBySVC(task_extractor, **kwargs)[source]

Corresponding to TaskDefinitionBySVC

Parameters:

task_extractor (Model) – SVC Model used to predicting target tasks

__call__(samples: sedna.datasources.BaseDataSource)[source]
class lib.sedna.algorithms.seen_task_learning.task_allocation.task_allocation.TaskAllocationByDataAttr(task_extractor, **kwargs)[source]

Corresponding to TaskDefinitionByDataAttr

Parameters:

  • task_extractor (Dict) – used to match target tasks

  • attr_filed (List[Metadata]) – metadata is usually a class feature label with a finite values.

__call__(samples: sedna.datasources.BaseDataSource)[source]
class lib.sedna.algorithms.seen_task_learning.task_allocation.task_allocation.TaskAllocationDefault(task_extractor, **kwargs)[source]

Task allocation specifically for unstructured data

Parameters:

task_extractor (Dict) – used to match target tasks

__call__(samples: sedna.datasources.BaseDataSource)[source]