isomap_manifold

Bases: manifold

Manifold learning using the Isomap algorithm.

This class implements dimensionality reduction using the Isomap algorithm, which preserves global geometric structure in the data.

Source code in tinybig/koala/manifold/manifold.py

class isomap_manifold(manifold):
    """
    Manifold learning using the Isomap algorithm.

    This class implements dimensionality reduction using the Isomap algorithm, which preserves global geometric
    structure in the data.
    """
    def __init__(self, name: str = 'isomap_manifold', *args, **kwargs):
        """
        Initialize the Isomap manifold learning class.

        Parameters
        ----------
        name : str, optional
            The name of the manifold learning method. Default is 'isomap_manifold'.
        *args, **kwargs
            Additional arguments for the base class.
        """
        super().__init__(name=name, *args, **kwargs)

    def init_model(self):
        """
        Initialize the Isomap model.
        """
        self.model = Isomap(n_neighbors=self.n_neighbors, n_components=self.n_components)

__init__(name='isomap_manifold', *args, **kwargs)

Initialize the Isomap manifold learning class.

Parameters:

Name	Type	Description	Default
name	str	The name of the manifold learning method. Default is 'isomap_manifold'.	'isomap_manifold'
*args		Additional arguments for the base class.	()
**kwargs		Additional arguments for the base class.	()

Source code in tinybig/koala/manifold/manifold.py

def __init__(self, name: str = 'isomap_manifold', *args, **kwargs):
    """
    Initialize the Isomap manifold learning class.

    Parameters
    ----------
    name : str, optional
        The name of the manifold learning method. Default is 'isomap_manifold'.
    *args, **kwargs
        Additional arguments for the base class.
    """
    super().__init__(name=name, *args, **kwargs)

init_model()

Initialize the Isomap model.

Source code in tinybig/koala/manifold/manifold.py

def init_model(self):
    """
    Initialize the Isomap model.
    """
    self.model = Isomap(n_neighbors=self.n_neighbors, n_components=self.n_components)