The update v0.3.3 has been released with additional features, API changes and fixes.
MAJOR: Multiobjective Framework: Affine Information Least Squares Algorithm (AILS)
Now you can use AILS to estimate parameters of NARMAX models (and variants) using a multiobjective approach.
AILS can be accessed using from sysidentpy.multiobjective_parameter_estimation import AILS
See the docs for a more in depth explanation of how to use AILS.
This feature is related to Issue #101. This work is the result of an undergraduate research conducted by Gabriel Bueno Leandro under the supervision of Samir Milani Martins and Wilson Rocha Lacerda Junior.
Several new methods were implemented to get the new feature and you can check all of it in sysidentpy -> multiobjective_parameter_estimation.
API Change: regressor_code variable was renamed as enconding to avoid using the same name as the method in narmax_toolregressor_code method.
DATASET: Added buck_id.csv and buck_valid.csv dataset to SysIdentPy repository.
DOC: Add a Multiobjetive Parameter Optimization Notebook showing how to use the new AILS method
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CHANGES
The update v0.3.3 has been released with additional features, API changes and fixes.
MAJOR: Multiobjective Framework: Affine Information Least Squares Algorithm (AILS)
from sysidentpy.multiobjective_parameter_estimation import AILSAPI Change:
regressor_codevariable was renamed asencondingto avoid using the same name as the method innarmax_toolregressor_codemethod.DATASET: Added buck_id.csv and buck_valid.csv dataset to SysIdentPy repository.
DOC: Add a Multiobjetive Parameter Optimization Notebook showing how to use the new AILS method
DOC: Minor additions and grammar fixes.