this post was submitted on 04 Dec 2023
1 points (100.0% liked)
Machine Learning
1 readers
1 users here now
Community Rules:
- Be nice. No offensive behavior, insults or attacks: we encourage a diverse community in which members feel safe and have a voice.
- Make your post clear and comprehensive: posts that lack insight or effort will be removed. (ex: questions which are easily googled)
- Beginner or career related questions go elsewhere. This community is focused in discussion of research and new projects that advance the state-of-the-art.
- Limit self-promotion. Comments and posts should be first and foremost about topics of interest to ML observers and practitioners. Limited self-promotion is tolerated, but the sub is not here as merely a source for free advertisement. Such posts will be removed at the discretion of the mods.
founded 1 year ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
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.