cxk | 让蔡徐坤在你的命令行里打篮球,使用 PHP 编写。
kandi X-RAY | cxk Summary
kandi X-RAY | cxk Summary
让蔡徐坤在你的命令行里打篮球,使用 PHP 编写。
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QUESTION
I have two matrices. One is of size (CxK) and another is of size (SxK) (where S,C, and K all have the potential to be very large). I want to combine these an output matrix using the cosine similarity function (would be of size [CxS]). When I run my code, it takes a very long time to produce an output, and I was wondering if there is any way to optimize what I currently have. [Note, the two input matrices are often very sparse]
I was previously traversing each matrix using two for index,row
loops, but I have since switched to the while loops, which improved my run time significantly.
ANSWER
Answered 2019-Aug-13 at 07:18This can be done much more easyly and way faster by passing the whole arrays to cosine_similarity
after you move the labels to the index:
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Install cxk
You can use cxk like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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