Examples of using Conditional probability in English and their translations into Russian
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In this case, the conditional probability of failure is not easy to calculate.
Exhaustive and mutually exclusive, dependent and independent,complementary events, conditional probability.
Unfortunately, in most applications, the conditional probability of failure is not easy to compute efficiently.
Basics of combinatorics(combinations, permutations) andprobability theory independence, conditional probability.
To keep the conditional probability of failure below 1, it suffices to keep the conditional expectation of F{\displaystyle F} below 1.
We want to be able to set each variable x s′{\displaystyle x'_{s}}in turn so as to keep the conditional probability of failure below 1.
To keep the conditional probability of failure below 1, it suffices to keep the conditional expectation of Q at or above the threshold|E|/2.
In the ideal case,given a partial state(a node in the tree), the conditional probability of failure(the label on the node) can be efficiently and exactly computed.
Since the conditional probability of failure is at most the conditional expectation of F{\displaystyle F}, in this way the algorithm ensures that the conditional probability of failure stays below 1.
Next, replace the random choice at each step by a deterministic choice,so as to keep the conditional probability of failure, given the vertices colored so far, below 1.
Bayes' theorem describes the conditional probability of an event based on data as well as prior information or beliefs about the event or conditions related to the event.
To apply the method of conditional probabilities, we need to extend the argument to bound the conditional probability of failure as the rounding step proceeds.
In this case,to keep the conditional probability of failure below 1, it suffices to keep the conditional expectation of Q below(or above) the threshold.
The CTW algorithm is an“ensemble method,” mixing the predictions of many underlying variable order Markov models,where each such model is constructed using zero-order conditional probability estimators.
Factors which affect the conditional probability of a certain sequence of events following a discharge of hazardous substances depend on the accident location and its surroundings.
This is because as long as the conditional expectation of Q is at least|E|/2, there must be some still-reachable outcome where Q is at least|E|/2,so the conditional probability of reaching such an outcome is positive.
Thus confidence can be interpreted as an estimate of the conditional probability P( E Y| E X){\displaystyle P( E_{ Y}| E_{ X})}, the probability of finding the RHS of the rule in transactions under the condition that these transactions also contain the LHS.
The authors conclude that, although the assumptions of the question run counter to observations, the paradox still has pedagogical value, since it"illustrates one of the more intriguing applications of conditional probability.
To apply the method of conditional probabilities, one focuses on the conditional probability of failure, given the choices so far as the experiment proceeds step by step.
If this is so, then the algorithm can select the next node to go to by computing the conditional probabilities at each of the children of the current node,then moving to any child whose conditional probability is less than 1.
The latter property is important because it implies that any interior node whose conditional probability is less than 1 has at least one child whose conditional probability is less than 1.
When applying the method of conditional probabilities, the technical term pessimistic estimator refers to a quantity used in place of the true conditional probability(or conditional expectation) underlying the proof.
Some models, such as logistic regression, are conditionally trained: they optimize the conditional probability Pr( Y| X){\displaystyle\Pr(Y\vert X)} directly on a training set see empirical risk minimization.
However, if the family was first selected and then a random, true statement was made about the sex of one child in that family, whether or not both were considered,the correct way to calculate the conditional probability is not to count all of the cases that include a child with that sex.
Since F≥ 1{\displaystyle F\geq 1} in any outcome where the rounding step fails,by Markov's inequality, the conditional probability of failure is at most the conditional expectation of F{\displaystyle F.
If the indicator gives a large number of„good‟ signals(i.e., has a high working capacity), we can expect that the probability of financial instability, if the alarm P(C|S)(conditional probability) is greater than the unconditional probability P C.
Definition in terms of joint and conditional probabilities edit.
Decompose the joint distribution break it into relevant independent or conditional probabilities.
This is usually needed when we want to calculate conditional probabilities, so we fix the value of the random variables we condition on.
In order toobtain statistically significant information on frequencies and conditional probabilities the demands increase further with regard to the number of accidents.