turicreate.toolkits.distances.squared_euclidean¶

turicreate.toolkits.distances.
squared_euclidean
(x, y)¶ Compute the squared Euclidean distance between two dictionaries or two lists of equal length. Suppose x and y each contain \(d\) variables:
\[D(x, y) = \sum_i^d (x_i  y_i)^2\]Parameters:  x : dict or list
First input vector.
 y : dict or list
Second input vector.
Returns:  out : float
Squared Euclidean distance between x and y.
Notes
 If the input vectors are in dictionary form, keys missing in one of the two dictionaries are assumed to have value 0.
 Squared Euclidean distance does not satisfy the triangle inequality, so it is not a metric. This means the ball tree cannot be used to compute nearest neighbors based on this distance.
References
Examples
>>> tc.distances.squared_euclidean([1, 2, 3], [4, 5, 6]) 27.0 ... >>> tc.distances.squared_euclidean({'a': 2, 'c': 4}, ... {'b': 3, 'c': 12}) 77.0