Quality measures

Warning

Some capabilities may require the installation of GEMSEO with all its features and some others may depend on plugins.

Warning

All the features of the wrapped libraries may not be exposed through GEMSEO.

F1Measure

Module: gemseo.mlearning.classification.quality.f1_measure

Required settings

• algo : BaseClassifier

  A machine learning algorithm for classification.

Optional settings

• fit_transformers : bool, optional

  Whether to re-fit the transformers when using resampling techniques. If False, use the transformers of the algorithm fitted from the whole learning dataset.

  By default it is set to True.

MAEMeasure

Module: gemseo.mlearning.regression.quality.mae_measure

Required settings

• algo : BaseRegressor

  A machine learning algorithm for supervised learning.

Optional settings

• fit_transformers : bool, optional

  Whether to re-fit the transformers when using resampling techniques. If False, use the transformers of the algorithm fitted from the whole learning dataset.

  By default it is set to False.

MEMeasure

Module: gemseo.mlearning.regression.quality.me_measure

Required settings

• algo : BaseRegressor

  A machine learning algorithm for supervised learning.

Optional settings

• fit_transformers : bool, optional

  Whether to re-fit the transformers when using resampling techniques. If False, use the transformers of the algorithm fitted from the whole learning dataset.

  By default it is set to False.

MSEMeasure

Module: gemseo.mlearning.regression.quality.mse_measure

Required settings

• algo : BaseRegressor

  A machine learning algorithm for regression.

Optional settings

• fit_transformers : bool, optional

  Whether to re-fit the transformers when using resampling techniques. If False, use the transformers of the algorithm fitted from the whole learning dataset.

  By default it is set to True.

R2Measure

Module: gemseo.mlearning.regression.quality.r2_measure

Required settings

• algo : BaseRegressor

  A machine learning algorithm for regression.

Optional settings

• fit_transformers : bool, optional

  Whether to re-fit the transformers when using resampling techniques. If False, use the transformers of the algorithm fitted from the whole learning dataset.

  By default it is set to True.

RMSEMeasure

Module: gemseo.mlearning.regression.quality.rmse_measure

Required settings

• algo : BaseRegressor

  A machine learning algorithm for regression.

Optional settings

• fit_transformers : bool, optional

  Whether to re-fit the transformers when using resampling techniques. If False, use the transformers of the algorithm fitted from the whole learning dataset.

  By default it is set to True.

SilhouetteMeasure

Module: gemseo.mlearning.clustering.quality.silhouette_measure

Required settings

• algo : BasePredictiveClusterer

  A clustering algorithm.

Optional settings

• fit_transformers : bool, optional

  Whether to re-fit the transformers when using resampling techniques. If False, use the transformers of the algorithm fitted from the whole learning dataset.

  By default it is set to True.