What I mean is:To decomposed Bayes’ Theorem into two illuminating parts:
The Prior (P(A)) – Your initial belief about A.
The Evidence Adjustment [P(B|A) / P(B)]– How much observing B rescales your belief in A.
This is Bayes’ Theorem in its easier understanding form:
Start with P(A), then adjust it by how strongly B points to A.
For me, it’s just a way of easier understanding Bayes.
What I mean is:
To decomposed Bayes’ Theorem into two illuminating parts:
The Prior (P(A)) – Your initial belief about A.
The Evidence Adjustment [P(B|A) / P(B)]– How much observing B rescales your belief in A.
This is Bayes’ Theorem in its easier understanding form:
Start with P(A), then adjust it by how strongly B points to A.
For me, it’s just a way of easier understanding Bayes.