小编Hug*_*cot的帖子

我使用余弦相似性在我的数据集上执行TSNE有一个小问题.

我已经计算了所有向量的余弦相似度,所以我有一个包含余弦相似度的方阵:

A = [[  1    0.7   0.5   0.6  ]
     [  0.7   1    0.3   0.4  ]
     [  0.5  0.3    1    0.1  ]
     [  0.6  0.4   0.1    1   ]]

然后,我正在使用TSNE:

A = np.matrix([[1, 0.7,0.5,0.6],[0.7,1,0.3,0.4],[0.5,0.3,1,0.1],[0.6,0.4,0.1,1]])
model = manifold.TSNE(metric="precomputed")
Y = model.fit_transform(A) 

但我不确定使用预先计算的度量标准来保持我的余弦相似度:

#[documentation][1]
If metric is “precomputed”, X is assumed to be a distance matrix

但是当我尝试使用余弦指标时,我收到了一个错误:

A = np.matrix([[1, 0.7,0.5,0.6],[0.7,1,0.3,0.4],[0.5,0.3,1,0.1],[0.6,0.4,0.1,1]])
model = manifold.TSNE(metric="cosine")
Y = model.fit_transform(A) 

raise ValueError("All distances should be positive, either "
ValueError: All distances should be positive, either the …