Bayesian Fact Quote by Pedro Domingos
““They point out that we never know for sure which hypothesis is the true one, and so we shouldn’t just pick one hypothesis, like a value of 0.7 for the probability of heads; rather, we should compute the posterior probability of every possible hypothesis and entertain all of them when making predictions. The sum of the probabilities of all the hypotheses must be one, so if one becomes more likely, the others become less. For a Bayesian, in fact, there is no such thing as the truth; you have a prior distribution over hypotheses, after seeing the data it becomes the posterior distribution, as given by Bayes’ theorem, and that’s all.””
About This Quote
Source Talk: Machine Learning Lecture, Pedro Domingos, 2015
Bayesian reasoning treats all hypotheses as possibilities, assigning probabilities that sum to one, updating them with data rather than seeking a single truth.
In simple terms: Bayes updates probabilities for all hypotheses based on data.
Key Takeaway
Use full probability distributions, not single estimates.
Themes
statistics
probability
decision making
uncertainty
Mood
analytical
thoughtful
Type
educational
philosophical
When to use this quote
- model selection
- risk assessment
- forecasting
- scientific research
Key Concepts
Bayesian inference
posterior distribution
prior belief
Questions to Reflect On
- How do you choose appropriate priors?
- What are the limits of Bayesian models?
A Different Perspective
Assumes correct model class and priors; computationally intensive for many hypotheses.
