a prior probability造句

• This finds the best value that simultaneously meets two conflicting objects : To perform as well as possible on the training data ( smallest Bayesian context, the regularization procedure can be viewed as placing a prior probability p ( \ boldsymbol \ theta ) on different values of \ boldsymbol \ theta.
• :: Another approach might be to again take a prior probability of 50 / 50 for whether the coin is biased, but take a beta distribution for the ( initially unknown ) probability of heads given a biased coin, which is then updated given the data . talk ) 22 : 37, 28 April 2013 ( UTC)
• The same applies to the event of typing a particular version of " Hamlet " followed by endless copies of itself; or " Hamlet " immediately followed by all the digits of pi; these specific strings are equally infinite in length, they are not prohibited by the terms of the thought problem, and they each have a prior probability of 0.
• :You don't need to have tossed it previously to have a prior probability in favour of it being fair-just looking at it and seeing that it has 6 sides which all look the same would suggest the chance of getting a 6 is about 1 / 6 ( unless you have a reason to believe any particular number if more likely than any other, you should assume otherwise ).
• They will put in a prior probability of 0 that you are breaking the laws of physics ( since an impossibility is automatically 0 ) and thus no matter what the result is, there will be 0 % confidence that you are actually doing what you say . . . If you get a positive test result, whatever the test, however many times you get it, it will always be a false positive due to the prior probability . . . but this plainly doesn't make any sense . . . ( in reality, if you get enough positive test results, you start attaching it to generators and start powering cities with it, you wouldn't just keep discarding positive test results . . . ).