hash2GloVe_test.py 文件源码

def distance(a,b):
    return scipy.spatial.distance.cosine(a,b) # ya incluye el 1-cos(ab)
    #return sum(pow(a[i]-b[i],2) for i in range(len(b))) #euclidean norm
    #pearson correlation in negative so lower is better
    #return 1- dot(norm(a),norm(b))
    #tanimoto distance
    #return 1 - dot(a,b)/(dot(a,a) + dot(b,b) - dot(a,b))
    #return sci.kendalltau(a,b) #kendall tau



# Load the benchmark