featuremapper/distribution.py
def _relative_second_selectivity(self, d):
        """
        Return the value of the second maximum as a proportion of the sum_value()
        see _relative_selectivity() for further details
        """
        k = d.max_value_bin()
        d.pop(k)
        m = max(d.values())
        d.restore(k)

        proportion = d._safe_divide(m, sum(d.values()))
        offset = 1.0 / len(d.data())
        scaled = (proportion - offset) / (1.0 - offset)

        return max(scaled, 0.0)

        Return the value of the second maximum as a proportion of the sum_value()
        see _relative_selectivity() for further details
        
Return the value of the second maximum as a proportion of the sum_value()
see _relative_selectivity() for further details
Return the value of the second maximum as a proportion of the sum_value () see _relative_selectivity () for further details
def _relative_second_selectivity(self, d):
        k = d.max_value_bin()
        d.pop(k)
        m = max(d.values())
        d.restore(k)
        proportion = d._safe_divide(m, sum(d.values()))
        offset = 1.0 / len(d.data())
        scaled = (proportion - offset) / (1.0 - offset)
        return max(scaled, 0.0)
def _relative_second_selectivity ( self , d ) : k = d . max_value_bin ( ) d . pop ( k ) m = max ( d . values ( ) ) d . restore ( k ) proportion = d . _safe_divide ( m , sum ( d . values ( ) ) ) offset = 1.0 / len ( d . data ( ) ) scaled = ( proportion - offset ) / ( 1.0 - offset ) return max ( scaled , 0.0 )
Return the value of the second maximum as a proportion of the sum_value()
see _relative_selectivity() for further details
Return the value of the second maximum as a proportion of the sum_value () see _relative_selectivity () for further details
"""
        Return the value of the second maximum as a proportion of the sum_value()
        see _relative_selectivity() for further details
        """
self
d