Options for Clustering algorithms

GaussianMixture

Module: gemseo.mlearning.cluster.gaussian_mixture

Here are the options available in GEMSEO:

Options
  • **parameters (Optional[Union[int,float,str,bool]])

    The parameters of the machine learning algorithm.

  • data (Dataset)

    The learning dataset.

  • n_components (int)

    The number of components of the Gaussian mixture.

    By default it is set to 5.

  • transformer (Optional[TransformerType])

    The strategies to transform the variables. The values are instances of Transformer while the keys are the names of either the variables or the groups of variables, e.g. “inputs” or “outputs” in the case of the regression algorithms. If a group is specified, the Transformer will be applied to all the variables of this group. If None, do not transform the variables.

    By default it is set to None.

  • var_names (Optional[Iterable[str]])

    The names of the variables. If None, consider all variables mentioned in the learning dataset.

    By default it is set to None.

KMeans

Module: gemseo.mlearning.cluster.kmeans

Here are the options available in GEMSEO:

Options
  • **parameters (Optional[Union[int,float,bool,str]])

    The parameters of the machine learning algorithm.

  • data (Dataset)

    The learning dataset.

  • n_clusters (int)

    The number of clusters of the K-means algorithm.

    By default it is set to 5.

  • random_state (Optional[int])

    If None, use a random generation of the initial centroids. If not None, the integer is used to make the initialization deterministic.

    By default it is set to 0.

  • transformer (Optional[TransformerType])

    The strategies to transform the variables. The values are instances of Transformer while the keys are the names of either the variables or the groups of variables, e.g. “inputs” or “outputs” in the case of the regression algorithms. If a group is specified, the Transformer will be applied to all the variables of this group. If None, do not transform the variables.

    By default it is set to None.

  • var_names (Optional[Iterable[str]])

    The names of the variables. If None, consider all variables mentioned in the learning dataset.

    By default it is set to None.

MLPredictiveClusteringAlgo

Module: gemseo.mlearning.cluster.cluster

Here are the options available in GEMSEO:

Options
  • **parameters (MLAlgoParameterType)

    The parameters of the machine learning algorithm.

  • data (Dataset)

    The learning dataset.

  • transformer (Optional[TransformerType])

    The strategies to transform the variables. The values are instances of Transformer while the keys are the names of either the variables or the groups of variables, e.g. “inputs” or “outputs” in the case of the regression algorithms. If a group is specified, the Transformer will be applied to all the variables of this group. If None, do not transform the variables.

    By default it is set to None.

  • var_names (Optional[Iterable[str]])

    The names of the variables. If None, consider all variables mentioned in the learning dataset.

    By default it is set to None.