Method l2_norm

pattern/vector/__init__.py:632–639

Yields the Frobenius matrix norm (cached). n = the square root of the sum of the absolute squares of the values. The matrix norm is used to normalize (0.0-1.0) cosine similarity between documents.

(self)

    
    @property
    def l2_norm(self):
        """ Yields the Frobenius matrix norm (cached).
            n = the square root of the sum of the absolute squares of the values.
            The matrix norm is used to normalize (0.0-1.0) cosine similarity between documents.
        """
        if self._norm is None: 
            self._norm = sum(w * w for w in self.itervalues()) ** 0.5
        return self._norm
        
    norm = l2 = L2 = L2norm = l2norm = L2_norm = l2_norm