(
        self,
        min_weight_for_similarity=0.1,
        min_count_for_similarity=2,
        similarity_exponent=4.0,
        shrinkage_value=0.0001,
        orientation="rows",
        verbose=False,
    )
Parameters
        ----------
        min_weight_for_similarity : float
            If sum of values in shared rows between two columns falls below this
            threhold then similarity can't be computed between those columns.

        min_count_for_similarity : int
            If number of overlapping rows between two columns falls below this
            threhold then similarity can't be computed between those columns.

        similarity_exponent : float
            Exponent for turning similarities into weights on values of other
            columns.

        shrinkage_value : float
            Shrinks reconstructed values toward 0

        orientation : str
            Whether to compute similarities along rows or columns

        verbose : bool
Parameters
        ----------
        min_weight_for_similarity : float
            If sum of values in shared rows between two columns falls below this
            threhold then similarity can't be computed between those columns.
Parameters ---------- min_weight_for_similarity : float If sum of values in shared rows between two columns falls below this threhold then similarity can t be computed between those columns .
def __init__(
        self,
        min_weight_for_similarity=0.1,
        min_count_for_similarity=2,
        similarity_exponent=4.0,
        shrinkage_value=0.0001,
        orientation="rows",
        verbose=False,
    ):
        """
        Parameters
        ----------
        min_weight_for_similarity : float
            If sum of values in shared rows between two columns falls below this
            threhold then similarity can't be computed between those columns.

        min_count_for_similarity : int
            If number of overlapping rows between two columns falls below this
            threhold then similarity can't be computed between those columns.

        similarity_exponent : float
            Exponent for turning similarities into weights on values of other
            columns.

        shrinkage_value : float
            Shrinks reconstructed values toward 0

        orientation : str
            Whether to compute similarities along rows or columns

        verbose : bool
        """
        self.min_weight_for_similarity = min_weight_for_similarity
        self.min_count_for_similarity = min_count_for_similarity
        self.similarity_exponent = similarity_exponent
        self.shrinkage_value = shrinkage_value
        self.orientation = orientation
        self.verbose = verbose
def __init__ ( self , min_weight_for_similarity = 0.1 , min_count_for_similarity = 2 , similarity_exponent = 4.0 , shrinkage_value = 0.0001 , orientation = "rows" , verbose = False , ) : self . min_weight_for_similarity = min_weight_for_similarity self . min_count_for_similarity = min_count_for_similarity self . similarity_exponent = similarity_exponent self . shrinkage_value = shrinkage_value self . orientation = orientation self . verbose = verbose