abacusai.algorithm
Classes
Customer created algorithm |
Module Contents
- class abacusai.algorithm.Algorithm(client, name=None, problemType=None, createdAt=None, updatedAt=None, isDefaultEnabled=None, trainingInputMappings=None, trainFunctionName=None, predictFunctionName=None, predictManyFunctionName=None, initializeFunctionName=None, configOptions=None, algorithmId=None, useGpu=None, algorithmTrainingConfig=None, onlyOfflineDeployable=None, codeSource={})
Bases:
abacusai.return_class.AbstractApiClassCustomer created algorithm
- Parameters:
client (ApiClient) – An authenticated API Client instance
name (str) – The name of the algorithm
problemType (str) – The type of the problem this algorithm will work on
createdAt (str) – When the algorithm was created
updatedAt (str) – When the algorithm was last updated
isDefaultEnabled (bool) – Whether train with the algorithm by default
trainingInputMappings (dict) – The mappings for train function parameters’ names, e.g. names for training data, name for training config
trainFunctionName (str) – Name of the function found in the source code that will be executed to train the model. It is not executed when this function is run.
predictFunctionName (str) – Name of the function found in the source code that will be executed run predictions through model. It is not executed when this function is run.
predictManyFunctionName (str) – Name of the function found in the source code that will be executed for batch prediction of the model. It is not executed when this function is run.
initializeFunctionName (str) – Name of the function found in the source code to initialize the trained model before using it to make predictions using the model
configOptions (dict) – Map dataset types and configs to train function parameter names
algorithmId (str) – The unique identifier of the algorithm
useGpu (bool) – Whether to use gpu for model training
algorithmTrainingConfig (dict) – The algorithm specific training config
onlyOfflineDeployable (bool) – Whether or not the algorithm is only allowed to be deployed offline
codeSource (CodeSource) – Info about the source code of the algorithm
- name
- problem_type
- created_at
- updated_at
- is_default_enabled
- training_input_mappings
- train_function_name
- predict_function_name
- predict_many_function_name
- initialize_function_name
- config_options
- algorithm_id
- use_gpu
- algorithm_training_config
- only_offline_deployable
- code_source
- deprecated_keys
- __repr__()