稀疏矩阵的点积

Question

Im reading implementation of the Multinomial Naive Bayes and I do not understand how does this following calculation of dot product of the following matrixes work.

self.feature_count_ += safe_sparse_dot(Y.T, X)

Code can be found here

Where YTshape = (3, 7000) and X.shape = (7000, 27860). How can it work when number of rows in the YT is not equal to number of columns in X ? The size of the resulting matrix is (3, 27860) ?? How does it work? What am I missing?

Answer 1

Check out the "Mulitplying a matrix by another matrix" section here: https://www.mathsisfun.com/algebra/matrix-multiplying.html

If you go through the multiplication, you'll see that only the "inner" dimensions have to match (the 7000 in your case)