An API for machine learning#
Machine learning functionalities.
This module proposes many high-level functions for creating and loading machine learning models.
- gemseo.mlearning.create_classification_model(name, data, transformer=mappingproxy({'inputs': <gemseo.mlearning.transformers.scaler.min_max_scaler.MinMaxScaler object>}), **parameters)[source]
Create a classification model from a learning dataset.
- Parameters:
name (str) -- The name of the classification algorithm.
data (IODataset) -- The learning dataset.
transformer (TransformerType) --
The strategies to transform the variables. Values are instances of
BaseTransformer
while keys are names of either variables or groups of variables. IfIDENTITY
, do not transform the variables.By default it is set to {'inputs': <gemseo.mlearning.transformers.scaler.min_max_scaler.MinMaxScaler object at 0x7fddbe694f70>}.
parameters -- The parameters of the classification model.
- Returns:
A classification model.
- Return type:
- gemseo.mlearning.create_clustering_model(name, data, transformer=mappingproxy({}), **parameters)[source]
Create a clustering model from a learning dataset.
- Parameters:
name (str) -- The name of the clustering algorithm.
data (Dataset) -- The learning dataset.
transformer (TransformerType) --
The strategies to transform the variables. Values are instances of
BaseTransformer
while keys are names of either variables or groups of variables. IfIDENTITY
, do not transform the variables.By default it is set to {}.
parameters -- The parameters of the clustering model.
- Returns:
A clustering model.
- Return type:
- gemseo.mlearning.create_mlearning_model(name, data, transformer=mappingproxy({}), **parameters)[source]
Create a machine learning algorithm from a learning dataset.
- Parameters:
name (str) -- The name of the machine learning algorithm.
data (Dataset) -- The learning dataset.
transformer (TransformerType) --
The strategies to transform the variables. Values are instances of
BaseTransformer
while keys are names of either variables or groups of variables. IfIDENTITY
, do not transform the variables.By default it is set to {}.
parameters -- The parameters of the machine learning algorithm.
- Returns:
A machine learning model.
- Return type:
- gemseo.mlearning.create_regression_model(name, data, transformer=mappingproxy({'inputs': <gemseo.mlearning.transformers.scaler.min_max_scaler.MinMaxScaler object>, 'outputs': <gemseo.mlearning.transformers.scaler.min_max_scaler.MinMaxScaler object>}), **parameters)[source]
Create a regression model from a learning dataset.
- Parameters:
name (str) -- The name of the regression algorithm.
data (IODataset) -- The learning dataset.
transformer (TransformerType) --
The strategies to transform the variables. Values are instances of
BaseTransformer
while keys are names of either variables or groups of variables. IfIDENTITY
, do not transform the variables.By default it is set to {'inputs': <gemseo.mlearning.transformers.scaler.min_max_scaler.MinMaxScaler object at 0x7fddbe6011f0>, 'outputs': <gemseo.mlearning.transformers.scaler.min_max_scaler.MinMaxScaler object at 0x7fddbe601400>}.
parameters -- The parameters of the regression model.
- Returns:
A regression model.
- Return type:
- gemseo.mlearning.get_classification_models()[source]
Get available classification models.
- gemseo.mlearning.get_classification_options(model_name, output_json=False, pretty_print=True)[source]
Find the available options for a classification model.
- Parameters:
- Returns:
The options schema of the classification model.
- Return type:
- gemseo.mlearning.get_clustering_models()[source]
Get available clustering models.
- gemseo.mlearning.get_clustering_options(model_name, output_json=False, pretty_print=True)[source]
Find the available options for a clustering model.
- Parameters:
- Returns:
The options schema of the clustering model.
- Return type:
- gemseo.mlearning.get_mlearning_models()[source]
Get available machine learning algorithms.
- gemseo.mlearning.get_mlearning_options(model_name, output_json=False, pretty_print=True)[source]
Find the available options for a machine learning algorithm.
- Parameters:
- Returns:
The options schema of the machine learning algorithm.
- Return type:
- gemseo.mlearning.get_regression_models()[source]
Get available regression models.
- gemseo.mlearning.get_regression_options(model_name, output_json=False, pretty_print=True)[source]
Find the available options for a regression model.
- Parameters:
- Returns:
The options schema of the regression model.
- Return type: