You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Right now in linalg.py, I'm using numpy.linalg.inv() for matrix inverses.
I'd like to implement it from scratch instead, but it looks rather difficult...
Note that Cholesky decomposition is only applicable to Hermitian matrices, which will work for PCA but hopefully I can also implement a more general-case algorithm like LUP decomposition as a fallback
Right now in
linalg.py
, I'm usingnumpy.linalg.inv()
for matrix inverses.I'd like to implement it from scratch instead, but it looks rather difficult...
Cholesky decomposition looks tractable, see:
The text was updated successfully, but these errors were encountered: