# scipy.spatial.distance.yule¶

scipy.spatial.distance.yule(u, v, w=None)[source]

Compute the Yule dissimilarity between two boolean 1-D arrays.

The Yule dissimilarity is defined as

$\frac{R}{c_{TT} * c_{FF} + \frac{R}{2}}$

where $$c_{ij}$$ is the number of occurrences of $$\mathtt{u[k]} = i$$ and $$\mathtt{v[k]} = j$$ for $$k < n$$ and $$R = 2.0 * c_{TF} * c_{FT}$$.

Parameters: u : (N,) array_like, bool Input array. v : (N,) array_like, bool Input array. w : (N,) array_like, optional The weights for each value in u and v. Default is None, which gives each value a weight of 1.0 yule : double The Yule dissimilarity between vectors u and v.

Examples

>>> from scipy.spatial import distance
>>> distance.yule([1, 0, 0], [0, 1, 0])
2.0
>>> distance.yule([1, 1, 0], [0, 1, 0])
0.0


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