Vladislav Ladenkov - 1 month ago 6x

Python Question

I am given a matrix of ones and zeros. I need to find 20 rows which have the highest cosine metrics towards 1

`specific`

If I have 10 rows, and 5th is called

`specific`

`cosine(1row,5row),cosine(2row,5row),...,cosine(8row,5row),cosine(9row,5row)`

First, i tried to count metrics.

This didn't work:

`A = ratings[:,100]`

A = A.reshape(1,A.shape[0])

B = ratings.transpose()

similarity = -cosine(A,B)+1

A.shape = (1L, 71869L)

B.shape = (10000L, 71869L)

Error is:

`Input vector should be 1-D.`

In my opinion, the fastest way is not realized with help of

`scipy`

We just have to take all ones in

`specific`

Are there any faster ways?

Answer

The fastest way is to use matrix operations: `something like np.multipy(A,B)`

Source (Stackoverflow)

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