featuremapper/distribution.py
def second_selectivity(self, d):
        """
        Return the selectivity of the second largest value in the distribution.
        If there is one feature_bin only, the selectivity is 0, since there is no second
        peack at all, and this value is also used to discriminate the validity
        of second_max_value_bin()
        Selectivity is computed in two ways depending on whether the variable is
        a cyclic, as in selectivity()
        """
        if len( d._data ) <= 1:
            return 0.0
        if d.cyclic == True:
            return self._vector_second_selectivity(d)
        else:
            return self._relative_second_selectivity(d)

        Return the selectivity of the second largest value in the distribution.
        If there is one feature_bin only, the selectivity is 0, since there is no second
        peack at all, and this value is also used to discriminate the validity
        of second_max_value_bin()
        Selectivity is computed in two ways depending on whether the variable is
        a cyclic, as in selectivity()
        
Return the selectivity of the second largest value in the distribution.
If there is one feature_bin only, the selectivity is 0, since there is no second
peack at all, and this value is also used to discriminate the validity
of second_max_value_bin()
Selectivity is computed in two ways depending on whether the variable is
a cyclic, as in selectivity()
Return the selectivity of the second largest value in the distribution . If there is one feature_bin only the selectivity is 0 since there is no second peack at all and this value is also used to discriminate the validity of second_max_value_bin () Selectivity is computed in two ways depending on whether the variable is a cyclic as in selectivity ()
def second_selectivity(self, d):
        if len( d._data ) <= 1:
            return 0.0
        if d.cyclic == True:
            return self._vector_second_selectivity(d)
        else:
            return self._relative_second_selectivity(d)
def second_selectivity ( self , d ) : if len ( d . _data ) <= 1 : return 0.0 if d . cyclic == True : return self . _vector_second_selectivity ( d ) else : return self . _relative_second_selectivity ( d )
Return the selectivity of the second largest value in the distribution.
Return the selectivity of the second largest value in the distribution .
"""
        Return the selectivity of the second largest value in the distribution.
        If there is one feature_bin only, the selectivity is 0, since there is no second
        peack at all, and this value is also used to discriminate the validity
        of second_max_value_bin()
        Selectivity is computed in two ways depending on whether the variable is
        a cyclic, as in selectivity()
        """
self
d