Fundamentals of Bayes’ Theorem
Bayes’ theorem uses three types of probabilities:
- Prior Probability (P(h)): Probability before observing any evidence.
- Likelihood Probability (P(E|h)): Probability of observing evidence given a hypothesis.
- Posterior Probability (P(h|E)): Updated probability of hypothesis after seeing evidence.
Bayes Theorem:
Classification Using Bayes Model
- Bayes theorem helps choose the most probable hypothesis from a set of hypotheses.
- It forms the basis for Naive Bayes Classifier.
