Artificial Intelligence, Lecture 6.1, Page 1
... A cab was involved in a hit-and-run accident at night. Two cab companies, the Green and the Blue, operate in the city. You are given the following data: The two companies operate the same number of cabs, but Green cabs are involved in 85% of the accidents. A witness identified the cab as Blue. The c ...
... A cab was involved in a hit-and-run accident at night. Two cab companies, the Green and the Blue, operate in the city. You are given the following data: The two companies operate the same number of cabs, but Green cabs are involved in 85% of the accidents. A witness identified the cab as Blue. The c ...
Neighbor selection and hitting probability in small
... is then trivially true that dH (x, y) is adapted for routing in G. The random edges need not be uniformly distributed, and indeed all the interesting cases arise when the probability of an edge being added between x and y depends on dH (x, y). Some independence is usually assumed, however, so that t ...
... is then trivially true that dH (x, y) is adapted for routing in G. The random edges need not be uniformly distributed, and indeed all the interesting cases arise when the probability of an edge being added between x and y depends on dH (x, y). Some independence is usually assumed, however, so that t ...
46656 Varieties of Bayesians (#765)
... All Bayesians, as I understand the term, believe that i t i s usually meaningful to talk about the probability of a hypothesis and they make some attempt to be consistent in their judgments. Thus von Mises (1942) would not count as a Bayesian, on this definition. For he considered that Bayes's theor ...
... All Bayesians, as I understand the term, believe that i t i s usually meaningful to talk about the probability of a hypothesis and they make some attempt to be consistent in their judgments. Thus von Mises (1942) would not count as a Bayesian, on this definition. For he considered that Bayes's theor ...
How bad is a 10% chance of losing a toe?
... candy. The probability distortions he found were later incorporated into prospect theory (Kahneman & Tversky, ...
... candy. The probability distortions he found were later incorporated into prospect theory (Kahneman & Tversky, ...
this paper - William M. Briggs
... refugee status in statistics, Franklin (2001). This is fully described Stove (1973, 1986). In any case, I do not follow Carnap’s terminology here, though I use deductive and non-deductive logic in what follows. The main purpose of this article is to survey the most common arguments used in assigning ...
... refugee status in statistics, Franklin (2001). This is fully described Stove (1973, 1986). In any case, I do not follow Carnap’s terminology here, though I use deductive and non-deductive logic in what follows. The main purpose of this article is to survey the most common arguments used in assigning ...
A Simple Sequential Algorithm for Approximating Bayesian Inference
... our criterion is satisfied, with q(hn+1 = h|d1 , ..., dn+1 ) = p(hn+1 = h|d1 , ..., dn+1 ) for any c such that φ ∈ [0, 1]. There are two interesting special cases to consider. The first arises when we take c = p(dn+1 |d1 , ..., dn+1 ). In this case, φ = p(dn+1 |hn+1 = h). This results in a simple al ...
... our criterion is satisfied, with q(hn+1 = h|d1 , ..., dn+1 ) = p(hn+1 = h|d1 , ..., dn+1 ) for any c such that φ ∈ [0, 1]. There are two interesting special cases to consider. The first arises when we take c = p(dn+1 |d1 , ..., dn+1 ). In this case, φ = p(dn+1 |hn+1 = h). This results in a simple al ...
Notes on Induction, Probability and Confirmation
... Issues in the Interpretation of Probability Though there has been little disagreement in relation to the mathematical formalism, there has been considerable controversy regarding the interpretation of the formalism—and in particular the meaning of the concept of probability. There have been two broa ...
... Issues in the Interpretation of Probability Though there has been little disagreement in relation to the mathematical formalism, there has been considerable controversy regarding the interpretation of the formalism—and in particular the meaning of the concept of probability. There have been two broa ...
“Your Honor, this was not a coincidence!”
... K similar crimes have been committed It has been proven beyond doubt that X committed one of them The court is allowed to conclude that X has committed all of them based on much less evidence than would normally be needed In principle, this makes sense also from a probabilistic point of view. But on ...
... K similar crimes have been committed It has been proven beyond doubt that X committed one of them The court is allowed to conclude that X has committed all of them based on much less evidence than would normally be needed In principle, this makes sense also from a probabilistic point of view. But on ...
Randomly Supported Independence and Resistance
... bits. Another problem that (almost) falls into this category is Max-Cut, in which t = 2 and P is non-equality. In traditional Max-Cut we do not allow negated literals and if we do allow negation the problem becomes Max-2-Lin-2, linear equations modulo 2 with two variables in each equation. These two ...
... bits. Another problem that (almost) falls into this category is Max-Cut, in which t = 2 and P is non-equality. In traditional Max-Cut we do not allow negated literals and if we do allow negation the problem becomes Max-2-Lin-2, linear equations modulo 2 with two variables in each equation. These two ...
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence... Stockholm, Sweden, August 1999
... to changes in the parameters. As usual, the likelihood of a parameter set is defined to be the probability of the data given the model: As usual, we typically work with the log of this function: ...
... to changes in the parameters. As usual, the likelihood of a parameter set is defined to be the probability of the data given the model: As usual, we typically work with the log of this function: ...
Probability box
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A probability box (or p-box) is a characterization of an uncertain number consisting of both aleatoric and epistemic uncertainties that is often used in risk analysis or quantitative uncertainty modeling where numerical calculations must be performed. Probability bounds analysis is used to make arithmetic and logical calculations with p-boxes.An example p-box is shown in the figure at right for an uncertain number x consisting of a left (upper) bound and a right (lower) bound on the probability distribution for x. The bounds are coincident for values of x below 0 and above 24. The bounds may have almost any shapes, including step functions, so long as they are monotonically increasing and do not cross each other. A p-box is used to express simultaneously incertitude (epistemic uncertainty), which is represented by the breadth between the left and right edges of the p-box, and variability (aleatory uncertainty), which is represented by the overall slant of the p-box.