Can someone help me understand how to rotate a vector A by some angle from vector B, both of size 512?
I have a feature vector that is compared to a basis vector which are the weights being updated, to do that an angle is calculated between the two vector’s and compared to ground truth. I would like reconstruct the feature vector by moving the basis vector by some angle, I’m not sure if rotation in higher dimensional space makes sense or if it’s better to try to learn that reconstruction
https://en.wikipedia.org/wiki/Rotation_matrix would be a great place to start to get a good idea of how you can use a rotation matrix to rotate a vector in 2 or 3 dimensions.
https://stackoverflow.com/questions/22099490/calculate-vector-after-rotating-it-towards-another-by-angle-θ-in-3d-space This post seems to be roughly what you’re looking for.
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To specify a rotation, you need both the axis of rotation, and the angle. Just the angle alone is ill-defined.
Even in 3D space, the number of vectors in a given angle to another vector are infinite, so which would you pick in an n dimensional space? In general calculating the angle between two vectors is a loss-introducing function (you take two sets of n numbers and condense it down to one). You can narrow it down to a set of N-1 linearly independent vectors that form a base of the given set of vectors in a given angle. Somebody with more linear algebra knowledge feel free to correct me.
/r/learnmachinelearning
That’s basic linear algebra