m m probability

Do projects sometimes get an activity or something, to let users participate, both to attract users to register, but also improve the user activity of the site. At the same time to participate in the user will receive a certain prize, there are 100% of winning, there is a certain probability of winning, big such as the ipad, small in a Q currency. Then we will certainly design the algorithm in the program, that is, in accordance with a certain

Original link: http://bbs.sciencenet.cn/thread-106012-1-1.htmlparticle size probability plot and particle size population (high slope rolling-jumping-suspension three-segment)The particle-size cumulative probability curve is an important phase mark used in sedimentary facies analysis, but most of the time only indicates that "a few sections of the main development of the high slope and low slope of such a d

: This article mainly introduces the php winning probability algorithm. if you are interested in the PHP Tutorial, you can refer to it. We will first complete the PHP process in the background. The main task of PHP is to configure the awards and the corresponding winning probability. when the front-end page clicks a box, we will want PHP to send ajax requests in the background, then, based on the configurat

Probabilistic algorithm for winning lottery programs written by PHP This article to share is the PHP winning probability algorithm, can be used for scraping cards, large turntable and other lottery algorithm. The usage is very simple, the code has the detailed comment explanation, one sees to understand, has the need small partner to refer to. We first completed the background PHP process, the main work of PHP is responsible for the allocation of pri

3.1 Two-Point Distribution and even distribution1. Two-Point DistributionMany random events have only two results. If the result of the product is qualified or unqualified, the product or reliable work may fail. This type of random event variable has only two values. Generally, 0 and 1 are used. It follows two-point distribution.Its probability distribution is:Where Pk = P (X = Xk) indicates the probability

In machine learning, we are usually interested in determining the best assumptions in hypothetical space H Given the training data D .The so-called best hypothesis, one approach is to define it as the most probable (most probable) hypothesis under the knowledge condition of the prior probabilities of different assumptions in the given data D and H .Bayesian theory provides a direct way to calculate this possibility. More precisely, the Bayes rule provides a method for calculating hypothetical pr

model we use, following our independent assumption of the same distribution. A model F with a parameter of θ produces the above sampling to be expressed asBack to the "model has been determined, parameters unknown," the statement, at this time, we know that, the unknown is θ, so the likelihood is defined as:　　In the actual application is commonly used in both sides to take the logarithm, the formula is as follows:This is called logarithmic likelihood, which is called the mean logarithmic likeli

PHP winning probability algorithm, can be used for scraping cards, large turntable and other lottery algorithm. The usage is very simple, the code has the detailed comment explanation, can understand at a glancePHP/** Classical probability algorithm, * $PROARR is a pre-set array, * Assuming array is: Array (100,200,300,400), * Start is to filter from 1,1000 this probabi