I believe 0 and 1 are probabilities, but there is no way to obtain that degree of certainty. (unless you have an incredibly clever method you aren’t sharing, which is mean)
An analogy would be that I believe that 3^^^3 is a number, even though I don’t think I will ever have that many dollars. Similarly, I believe that 0 and 1 are probabilities, but I wouldn’t grant any particular belief a probability of 0 or 1.
I’d like to point out that anyone who does not share the (claimed) Infinite Certainty should be upvoting, as this confidence level is infinitely higher than any other possible confidence level. (It’s kind of like, if you agree that dividing by zero is merely an error, then any claim to infinite certainty is also an error, almost exactly the same error in fact.)
Does this belief really affect anything, or is it only a proposition considered true without any consequences on your cognitive processes? (I’ve always regarded “0 and 1 are not probabilities” as more of a rhetorical figure than a statement of belief.)
That’s not really it, though, because I think the “0 and 1 are not probabilities” claim is really about degrees of belief in non-mathematical propositions. In its most-reasonable-to-me form, it says something like “Even if you have an argument that statement S is true with probability 1, you should believe Pr[S] < 1, because your argument could be wrong”. And there’s… really not a lot I could say in response to that. Except I would note that the value 1 isn’t really special here.
But there’s a lot of things that go together with this idea that I do disagree with. In very many senses, even non-mathematical propositions do end up having probabilities of 0 or 1. For instance:
Any time we deal with (even theoretical) infinities (this one is important because here we get events with probability 0 that can actually happen)
Tautologies (duh)
Conditional probabilities (nobody really disagrees with this, but I think lots of probabilities we think are unconditional aren’t)
Any belief that I can never be talked out of (given how the human mind works, probably most beliefs we have are like this actually)
Plus in practice accepting “0 and 1 are not probabilities” rhetorically or otherwise just means that you stop writing 1 and start writing 1-epsilon. Whose belief is it really that doesn’t affect anything?
even non-mathematical propositions do end up having probabilities of 0 or 1 … Tautologies
Tautologies are true for mathematical reasons and there is little difference—as far as probability assessment goes—between “P ∨ ∽P” and “Yding Skovhøj is the highest peak of Egypt or Yding Skovhøj is not the highest peak of Egypt”. Thus, tautologies (and pseudologies, or how do we call their false counterparts) don’t really make a category distinct from mathematical statements.
Conditional probabilities
I am not sure what you mean here. Of course there are conditional probabilities of form “if X, then X”, but they already belong to the tautology group.
Regarding mathematical statements it’s nevertheless important to notice that there are two meanings of “probability”. First, there is what I would call “idealised” or “mathematical probability”, formally defined inside a mathematical theory. One typically defines probability as a measure over some abstract space and usually is able to prove that there exist sets of probability 1 or 0. This is, more or less, the sort of probability relevant to the probabilistic method you have linked to. Second, there is the “psychological” probability which has the intuitive meaning of “degree of belief”, where 1 and 0 refer to absolute certainty. This is, more or less, the sort of probability spoken about in “1 and 0 aren’t probabilities”.
These two kinds of probabilities may correspond to each other more or less closely, but aren’t the same: having a formal proof of a proposition isn’t the same as being absolutely certain about it; people make mistakes when checking proofs.
Plus in practice accepting “0 and 1 are not probabilities” rhetorically or otherwise just means that you stop writing 1 and start writing 1-epsilon. Whose belief is it really that doesn’t affect anything?
If believing P doesn’t affect anything, then naturally believing non-P doesn’t affect anything either. So, if you agree that “1 and 0 aren’t probabilities” is an inconsequential belief, does it mean that your answer to my original question is “yes”?
If believing P doesn’t affect anything, then naturally believing non-P doesn’t affect anything either. So, if you agree that “1 and 0 aren’t probabilities” is an inconsequential belief, does it mean that your answer to my original question is “yes”?
Saying that my belief in P is inconsequential implies that actually I am acting as if I believed not-P, even though I profess a belief in P. I argue that, conversely, many people who profess a belief in not-P act as if they actually believe P.
The point is that “acting as if one believes P” and “acting as if one believes not-P” can sometimes be the same actings. This is what I meant by “inconsequential”. I want to know whether, in your opinion, this is such a situation; that is, whether there is some imaginable behaviour (other than professing the belief) which would make sense if one believed that “1 is not a probability” but would not make sense if one believed otherwise.
Any belief that I can never be talked out of (given how the human mind works, probably most beliefs we have are like this actually)
I suspect that with enough resources you could be talked out of any of your beliefs. Oh, sure, it would take a lot of time, planning, and manpower (and probably some people you approve of having the beliefs we’d want to indoctrinate you with). You’re not actually 100% certain that you’re 100% certain that 0 and 1 are probabilities.
The trouble with thinking 0 or 1 is a probability is that it is exactly equivalent to having an infinite amount of evidence, which is impossible by the laws of thermodynamics; minds exist within physics.
Furthermore, a feeling of absolute certainty isn’t even a number, much less a probability.
I suspect that with enough resources you could be talked out of any of your beliefs.
At some point you have to ask: who is this “me” that can have any arbitrary collection of beliefs?
(And yes, incidentally, I don’t assign 100% probability to the fact that I assign 100% probability to the statement “0 and 1 are probabilities.” I think I could be persuaded, not to have a lower confidence in the 0-1 statement, but to believe that my confidence in it is lower than it is. This is sort of hard to think about, though.)
This doesn’t offer any anticipation about the world for me to agree or disagree with. Probability is just a formalism you use, and there’s no reason for you to not define the formalism anyway you want.
I’m not quite sure how to parse that, but I’ll do my best. I am more confident in math than I am in my belief that arbitrary parts of my life are not hallucinations.
Damn… You’re good. Anyway, 1 and 0 aren’t probabilities because Bayes Theorem break down there (in the log-odds/information base where Bayes Theorem is simple addition, they are positive and negative infinity). You can however meaningfully construct limits of probabilities. I prefer the notation (1 -) epsilon.
Log-odds aren’t what probability is, they’re a way to think about probability. They happen not to work so well when the probabilities are 0 and 1; they also fail rather dramatically for probability density functions. That doesn’t mean they don’t have their uses.
Similarly, Bayes’s Theorem breaks down because the proof of it assumes a nonzero probability. This isn’t fixed by defining away 0 and 1, because it can still return those as output, and then you end up looking silly. In many cases, not being able to condition on an event with probability 0 is the only thing to do: given that a d6 comes up both odd and even, what is the probability that the result is higher than 3?
[I tried saying some things about conditioning on sets of measure 0 here, but apparently I don’t know what I’m talking about so I will retract that portion of the comment for the sake of clarity.]
Log-odds are perfectly isomorphic with probabilities and satisfies Cox’s Theorem. Saying that log-odds are not what probabilities are is as non-sequiteur as saying 2+2 isn’t a valid representation of 4.
Bayes theorem assumes no such thing as non-zero probability, it assumes Real Numbered probabilities, as it is in fact a perfectly valid statement of real-number arithmetic in any other context. It just so happens to be that this arithmetic expression is undefined for when certain variables are 0, and is an identity (equal to 1) when certain variables are 1. Neither are particularly interesting.
Bayes Theorem is interesting because it becomes propositional logic when you apply it to a limit going towards 1 or 0.
Real life applications are not my expertise, but I know my groups, categories and types. 0 and 1 are not probabilities, just as positive and negative infinity are not Real Numbers. This is a truth derived directly from Russel’s Axioms, which is the definition basis for all modern mathematics.
When you say P(A) = 1 you are not using probabilities anymore, At best your are doing propositional logic, at worst you’ll get a type error. If you want to be as sure as you can, let credence be 1 - epsilon for arbitrarily small positive real epsilon.
Clearly log-odds aren’t perfectly isomorphic with multiplicative probabilities, since clearly one allows probabilities of 0 and 1 and the other doesn’t.
Bayes’s theorem does assume nonzero probability, as you can observe by examining its proof.
Pr[A & B] = Pr[B] Pr[A|B] = Pr[A] Pr[B|A] by definition of conditional probability.
Pr[A|B] = Pr[A] Pr[B|A] / Pr[B] if we divide by Pr[B]. This assumes Pr[B]>0 because otherwise this operation is invalid.
You can’t derive properties of probability from Russell’s axioms, because these describe set theory and not probability. One standard way of deriving properties of probability is via Dutch Book arguments. These can only show that probabilities must be in the range [0,1] (including the endpoints). In fact, no finite sequence of bets you offer me can distinguish a credence of 1 from a credence of 1-epsilon for sufficiently small epsilon. (That is, for any epsilon, there’s a bet that distinguishes 1-epsilon from 1, but for any sequence of bets, there’s an 1-epsilon that is indistinguishable from 1).
Here is an analogy. The well-known formula D = RT describes the relationship between distance traveled, average speed, and time. You can also express this as log(D) = log(R) + log(T) if you like, or D/R = T. In either of these formulas, setting R=0 will be an error. This doesn’t mean that there’s no such thing as a speed of 0, and if you think your speed is 0 you are actually traveling at a speed of epsilon for some very small value of epsilon. It just means that when you passed to these (mostly equivalent) formulations, you lost the capability to discuss speeds of 0. In fact, when we set R to 0 in the original formula, we get a more useful description of what happens: D=0 no matter the value of T. In other words, 0 is a valid speed, but you can’t travel a nonzero distance with an average speed of zero, no matter how much time you allow yourself.
What is the difference between log-odds and log-speeds, that makes the former an isomorphism and the latter an imperfect description?
Finally, do you really think that someone who thinks “0 and 1 are probabilities” is a statement LW is irrational about is unaware of the “0 and 1 are not probabilities” post?
By virtue of the definition of a logarithm, exp(log(x)) = x, we can derive that since the exponential function is well-defined for complex numbers, so is the logarithm. Taking the logarithm of a negative number nets you the logarithm of the absolute plus imaginary pi. The real part of any logarithm is a symmetric function, and there are probably a few other interesting properties of logarithms in complex analysis that I don’t know of.
log(0) is undefined, as you note, but that does not mean the limit x → 0 log(x) is undefined. It is in fact a pole singularity (if I have understood my singularity analysis correct). No matter how you approach it, you get negative infinity. So given your “logarithmic velocities,” I counter with the fact that using a limit it is still a perfect isomorphism. Limit of x → -inf exp(x) is indeed 0, so when using limits (which is practically what Real Numbers are for) your argument that log isn’t an isomophism from reals to reals is hereby proven invalid (if you want a step by step proof, just ask, it’ll be a fun exercise).
Given that logarithms are a category-theoretic isomorphism from the reals onto the reals (from the multiplication group onto the addition group) there is no reason why log-odds isn’t as valid as odds, which is as valid as ]0,1[ probabilities. Infinities are not valid Reals, 0 and 1 are not valid probablities QED.
As I said. Do not challenge anyone (including me) on the abstract algebra of the matter.
[I do apologize if the argument is poorly formulated, I am as of writing mildly intoxicated]
Yes, log(x) is an isomorphism from the positive reals as a multiplicative group to the real numbers as an additive group. As a result, it is only an isomorphism from multiplicative probabilities to additive log-probabilities if you assume that 0 is not a probability to begin with, which is circular logic.
To obtain paradoxes, it is you that would need access to more proofs than I do.
From an evidence-based point of view, as a contrapositive of the usual argument against P=0 and P=1, we can say that if it’s possible to convince me that a statement might be false, it must be that I already assign it probability strictly <1.
As you may have guessed, I also don’t agree with the point of view that I can be convinced of the truth of any statement, even given arbitrarily bizarre circumstances. I believe that one needs rules by which to reason. Obviously these can be changed, but you need meta-rules to describe how you change rules, and possibly meta-meta-rules as well, but there must be something basic to use.
So I assign P=1 to things that are fundamental to the way I think about the world. In my case, this includes the way I think about probability.
In more mathematical settings, you can successfully condition on events with probability 0 (for instance, if (X,Y) follow a bivariate normal distribution, you might want to know the probability distribution of Y given X=x).
You can’t really do this, since the answer depends on how you take the limit. You can find a limit of conditional probabilities, but saying “the probability distribution of Y given X=x” is ambiguous. This is known as the Borel-Kolmogorov paradox.
I’d not seen Elizier’s post on “0 and 1 are not probabilities” before. It was a very interesting point. The link at the end was very amusing.
However, it seems he meant “it would be more useful to define probabilities excluding 0 and 1” (which may well be true), but phrased it as if it were a statement of fact. I think this is dangerous and almost always counterproductive—if you mean “I think you are using these words wrong” you should say that, not give the impression you mean “that statement you made with those words is false according to your interpretation of those words is false”.
Upvoted in furious, happy disagreement, because I was going to post this very thing, with a confidence level of 20%, but then I reasoned out that this was unbelievably stupid and the probability of infinite Bayesian evidence being possible should be the same as probabilities for other things we have very strong reason to believe are simply impossible: 1 - epsilon.
I do believe the 100% thing, though. It’s just that in this case, karma is not maximized where spirit-of-the-game is maximized, and I thought I’d point that out.
Gaining utility from karma, illegitemate or fraudulent sources regardless, is an ongoing problem which never ceases to amuse me. Let the humans have their fun!
Irrationality game
0 and 1 are probabilities. (100%)
Upvoted not for the claim, but the ridiculously high confidence in that claim.
Are you saying that you probably agree that 0 and 1 are probabilities, but my claim is not one of the things you would assign a probability of 1 to?
I believe 0 and 1 are probabilities, but there is no way to obtain that degree of certainty. (unless you have an incredibly clever method you aren’t sharing, which is mean)
An analogy would be that I believe that 3^^^3 is a number, even though I don’t think I will ever have that many dollars. Similarly, I believe that 0 and 1 are probabilities, but I wouldn’t grant any particular belief a probability of 0 or 1.
My intention was to make a stronger claim than the one you agree with, but fortunately my degree of confidence takes care of that for me.
I’d like to point out that anyone who does not share the (claimed) Infinite Certainty should be upvoting, as this confidence level is infinitely higher than any other possible confidence level. (It’s kind of like, if you agree that dividing by zero is merely an error, then any claim to infinite certainty is also an error, almost exactly the same error in fact.)
Nothing we can say will change your mind, unless already don’t believe this.
Downvoted for agreement. Trivially, P(A|A)=1 and P(A|~A)=0.
Does this belief really affect anything, or is it only a proposition considered true without any consequences on your cognitive processes? (I’ve always regarded “0 and 1 are not probabilities” as more of a rhetorical figure than a statement of belief.)
Well, on a somewhat trivial note, I (plan to) make my living proving that certain things have probabilities distinct from 0, so if 0 and 1 weren’t probabilities to begin with I’d be out of a job.
That’s not really it, though, because I think the “0 and 1 are not probabilities” claim is really about degrees of belief in non-mathematical propositions. In its most-reasonable-to-me form, it says something like “Even if you have an argument that statement S is true with probability 1, you should believe Pr[S] < 1, because your argument could be wrong”. And there’s… really not a lot I could say in response to that. Except I would note that the value 1 isn’t really special here.
But there’s a lot of things that go together with this idea that I do disagree with. In very many senses, even non-mathematical propositions do end up having probabilities of 0 or 1. For instance:
Any time we deal with (even theoretical) infinities (this one is important because here we get events with probability 0 that can actually happen)
Tautologies (duh)
Conditional probabilities (nobody really disagrees with this, but I think lots of probabilities we think are unconditional aren’t)
Any belief that I can never be talked out of (given how the human mind works, probably most beliefs we have are like this actually)
Plus in practice accepting “0 and 1 are not probabilities” rhetorically or otherwise just means that you stop writing 1 and start writing 1-epsilon. Whose belief is it really that doesn’t affect anything?
Tautologies are true for mathematical reasons and there is little difference—as far as probability assessment goes—between “P ∨ ∽P” and “Yding Skovhøj is the highest peak of Egypt or Yding Skovhøj is not the highest peak of Egypt”. Thus, tautologies (and pseudologies, or how do we call their false counterparts) don’t really make a category distinct from mathematical statements.
I am not sure what you mean here. Of course there are conditional probabilities of form “if X, then X”, but they already belong to the tautology group.
Regarding mathematical statements it’s nevertheless important to notice that there are two meanings of “probability”. First, there is what I would call “idealised” or “mathematical probability”, formally defined inside a mathematical theory. One typically defines probability as a measure over some abstract space and usually is able to prove that there exist sets of probability 1 or 0. This is, more or less, the sort of probability relevant to the probabilistic method you have linked to. Second, there is the “psychological” probability which has the intuitive meaning of “degree of belief”, where 1 and 0 refer to absolute certainty. This is, more or less, the sort of probability spoken about in “1 and 0 aren’t probabilities”.
These two kinds of probabilities may correspond to each other more or less closely, but aren’t the same: having a formal proof of a proposition isn’t the same as being absolutely certain about it; people make mistakes when checking proofs.
If believing P doesn’t affect anything, then naturally believing non-P doesn’t affect anything either. So, if you agree that “1 and 0 aren’t probabilities” is an inconsequential belief, does it mean that your answer to my original question is “yes”?
Saying that my belief in P is inconsequential implies that actually I am acting as if I believed not-P, even though I profess a belief in P. I argue that, conversely, many people who profess a belief in not-P act as if they actually believe P.
The point is that “acting as if one believes P” and “acting as if one believes not-P” can sometimes be the same actings. This is what I meant by “inconsequential”. I want to know whether, in your opinion, this is such a situation; that is, whether there is some imaginable behaviour (other than professing the belief) which would make sense if one believed that “1 is not a probability” but would not make sense if one believed otherwise.
I suspect that with enough resources you could be talked out of any of your beliefs. Oh, sure, it would take a lot of time, planning, and manpower (and probably some people you approve of having the beliefs we’d want to indoctrinate you with). You’re not actually 100% certain that you’re 100% certain that 0 and 1 are probabilities.
The trouble with thinking 0 or 1 is a probability is that it is exactly equivalent to having an infinite amount of evidence, which is impossible by the laws of thermodynamics; minds exist within physics.
Furthermore, a feeling of absolute certainty isn’t even a number, much less a probability.
At some point you have to ask: who is this “me” that can have any arbitrary collection of beliefs?
(And yes, incidentally, I don’t assign 100% probability to the fact that I assign 100% probability to the statement “0 and 1 are probabilities.” I think I could be persuaded, not to have a lower confidence in the 0-1 statement, but to believe that my confidence in it is lower than it is. This is sort of hard to think about, though.)
Funny.
This doesn’t offer any anticipation about the world for me to agree or disagree with. Probability is just a formalism you use, and there’s no reason for you to not define the formalism anyway you want.
So you are more confident in math than in hallucinating this entire interaction with an internet forum?
I’m not quite sure how to parse that, but I’ll do my best. I am more confident in math than I am in my belief that arbitrary parts of my life are not hallucinations.
Damn… You’re good. Anyway, 1 and 0 aren’t probabilities because Bayes Theorem break down there (in the log-odds/information base where Bayes Theorem is simple addition, they are positive and negative infinity). You can however meaningfully construct limits of probabilities. I prefer the notation (1 -) epsilon.
Log-odds aren’t what probability is, they’re a way to think about probability. They happen not to work so well when the probabilities are 0 and 1; they also fail rather dramatically for probability density functions. That doesn’t mean they don’t have their uses.
Similarly, Bayes’s Theorem breaks down because the proof of it assumes a nonzero probability. This isn’t fixed by defining away 0 and 1, because it can still return those as output, and then you end up looking silly. In many cases, not being able to condition on an event with probability 0 is the only thing to do: given that a d6 comes up both odd and even, what is the probability that the result is higher than 3?
[I tried saying some things about conditioning on sets of measure 0 here, but apparently I don’t know what I’m talking about so I will retract that portion of the comment for the sake of clarity.]
Log-odds are perfectly isomorphic with probabilities and satisfies Cox’s Theorem. Saying that log-odds are not what probabilities are is as non-sequiteur as saying 2+2 isn’t a valid representation of 4.
Bayes theorem assumes no such thing as non-zero probability, it assumes Real Numbered probabilities, as it is in fact a perfectly valid statement of real-number arithmetic in any other context. It just so happens to be that this arithmetic expression is undefined for when certain variables are 0, and is an identity (equal to 1) when certain variables are 1. Neither are particularly interesting.
Bayes Theorem is interesting because it becomes propositional logic when you apply it to a limit going towards 1 or 0.
Real life applications are not my expertise, but I know my groups, categories and types. 0 and 1 are not probabilities, just as positive and negative infinity are not Real Numbers. This is a truth derived directly from Russel’s Axioms, which is the definition basis for all modern mathematics.
When you say P(A) = 1 you are not using probabilities anymore, At best your are doing propositional logic, at worst you’ll get a type error. If you want to be as sure as you can, let credence be 1 - epsilon for arbitrarily small positive real epsilon.
1 and 0 are not probabilities by definition
Clearly log-odds aren’t perfectly isomorphic with multiplicative probabilities, since clearly one allows probabilities of 0 and 1 and the other doesn’t.
Bayes’s theorem does assume nonzero probability, as you can observe by examining its proof.
Pr[A & B] = Pr[B] Pr[A|B] = Pr[A] Pr[B|A] by definition of conditional probability.
Pr[A|B] = Pr[A] Pr[B|A] / Pr[B] if we divide by Pr[B]. This assumes Pr[B]>0 because otherwise this operation is invalid.
You can’t derive properties of probability from Russell’s axioms, because these describe set theory and not probability. One standard way of deriving properties of probability is via Dutch Book arguments. These can only show that probabilities must be in the range [0,1] (including the endpoints). In fact, no finite sequence of bets you offer me can distinguish a credence of 1 from a credence of 1-epsilon for sufficiently small epsilon. (That is, for any epsilon, there’s a bet that distinguishes 1-epsilon from 1, but for any sequence of bets, there’s an 1-epsilon that is indistinguishable from 1).
Here is an analogy. The well-known formula D = RT describes the relationship between distance traveled, average speed, and time. You can also express this as log(D) = log(R) + log(T) if you like, or D/R = T. In either of these formulas, setting R=0 will be an error. This doesn’t mean that there’s no such thing as a speed of 0, and if you think your speed is 0 you are actually traveling at a speed of epsilon for some very small value of epsilon. It just means that when you passed to these (mostly equivalent) formulations, you lost the capability to discuss speeds of 0. In fact, when we set R to 0 in the original formula, we get a more useful description of what happens: D=0 no matter the value of T. In other words, 0 is a valid speed, but you can’t travel a nonzero distance with an average speed of zero, no matter how much time you allow yourself.
What is the difference between log-odds and log-speeds, that makes the former an isomorphism and the latter an imperfect description?
Finally, do you really think that someone who thinks “0 and 1 are probabilities” is a statement LW is irrational about is unaware of the “0 and 1 are not probabilities” post?
Potholing that last sentence was mostly for fun.
By virtue of the definition of a logarithm, exp(log(x)) = x, we can derive that since the exponential function is well-defined for complex numbers, so is the logarithm. Taking the logarithm of a negative number nets you the logarithm of the absolute plus imaginary pi. The real part of any logarithm is a symmetric function, and there are probably a few other interesting properties of logarithms in complex analysis that I don’t know of.
log(0) is undefined, as you note, but that does not mean the limit x → 0 log(x) is undefined. It is in fact a pole singularity (if I have understood my singularity analysis correct). No matter how you approach it, you get negative infinity. So given your “logarithmic velocities,” I counter with the fact that using a limit it is still a perfect isomorphism. Limit of x → -inf exp(x) is indeed 0, so when using limits (which is practically what Real Numbers are for) your argument that log isn’t an isomophism from reals to reals is hereby proven invalid (if you want a step by step proof, just ask, it’ll be a fun exercise).
Given that logarithms are a category-theoretic isomorphism from the reals onto the reals (from the multiplication group onto the addition group) there is no reason why log-odds isn’t as valid as odds, which is as valid as ]0,1[ probabilities. Infinities are not valid Reals, 0 and 1 are not valid probablities QED.
As I said. Do not challenge anyone (including me) on the abstract algebra of the matter.
[I do apologize if the argument is poorly formulated, I am as of writing mildly intoxicated]
Yes, log(x) is an isomorphism from the positive reals as a multiplicative group to the real numbers as an additive group. As a result, it is only an isomorphism from multiplicative probabilities to additive log-probabilities if you assume that 0 is not a probability to begin with, which is circular logic.
So, pray tell: When are P=0 and P=1 applicable? Don’t you get paradoxes? What prior allows you to attain them?
I am really genuinely curious what sort of proofs you have access to that I do not.
To obtain paradoxes, it is you that would need access to more proofs than I do.
From an evidence-based point of view, as a contrapositive of the usual argument against P=0 and P=1, we can say that if it’s possible to convince me that a statement might be false, it must be that I already assign it probability strictly <1.
As you may have guessed, I also don’t agree with the point of view that I can be convinced of the truth of any statement, even given arbitrarily bizarre circumstances. I believe that one needs rules by which to reason. Obviously these can be changed, but you need meta-rules to describe how you change rules, and possibly meta-meta-rules as well, but there must be something basic to use.
So I assign P=1 to things that are fundamental to the way I think about the world. In my case, this includes the way I think about probability.
You can’t really do this, since the answer depends on how you take the limit. You can find a limit of conditional probabilities, but saying “the probability distribution of Y given X=x” is ambiguous. This is known as the Borel-Kolmogorov paradox.
Oops. Right, I knew there were some problems here, but I thought the way I defined it I was safe. I guess not. Thanks for keeping me honest!
I’d not seen Elizier’s post on “0 and 1 are not probabilities” before. It was a very interesting point. The link at the end was very amusing.
However, it seems he meant “it would be more useful to define probabilities excluding 0 and 1” (which may well be true), but phrased it as if it were a statement of fact. I think this is dangerous and almost always counterproductive—if you mean “I think you are using these words wrong” you should say that, not give the impression you mean “that statement you made with those words is false according to your interpretation of those words is false”.
Only Sith deal in absolutes!
I am very happy that the parent is currently at 0 karma.
Upvoted in furious, happy disagreement, because I was going to post this very thing, with a confidence level of 20%, but then I reasoned out that this was unbelievably stupid and the probability of infinite Bayesian evidence being possible should be the same as probabilities for other things we have very strong reason to believe are simply impossible: 1 - epsilon.
I’m pretty sure the probability of almost certainly impossible things being possible is lower than 1-epsilon. Except for very large values of epsilon.
Indeed, for values of epsilon approaching one.
I suppose if I wanted to maximize karma I should have stated a confidence level of 0%.
You’re supposed to post things you actually believe, you know! What are you, a spirit-of-the-game violator?
I do believe the 100% thing, though. It’s just that in this case, karma is not maximized where spirit-of-the-game is maximized, and I thought I’d point that out.
Gaining utility from karma, illegitemate or fraudulent sources regardless, is an ongoing problem which never ceases to amuse me. Let the humans have their fun!
Downvoted for agreement. Of course usually it isn’t rational to assign probabilites of 0 and 1, but in this case I think it is.