我都进球了，1间用户5，一个音乐项目， 我需要一个公式来获得最高的5计分项目。

I have an music items that are scored by users between 1 to 5, and I need a formula to get the 5 most scored items.

但显然是得到3.5平均得分从1000不同用户的项目将被更多的得分，然后一个项目泰德得到4.9平均得分仅5个用户......换句话说，我认为，如果一个项目获得关注的人得分它，这表示该项目是有趣。因此在计算中votesCount参数需要有一个电源。 （多大的权力？我不知道，我问它，你得到的想法）。

But obviously an item that get 3.5 average score from 1000 different users will be more scored then an item thet get 4.9 average score from only 5 users... in other words I think that if an item get attention from people to score it, this indicates that the item is interesting. so in the calculation the votesCount parameter need to have a power. (how much power? I don't sure, and I asking it you to get ideas).

我认为，我们需要以下参数功能：votesAverage，votesCount。

I think that we need the following parameters in the function: votesAverage, votesCount.

推荐答案

您可以使用贝叶斯估计来计算加权投票。

Weighted voting for 5-star systems with lots of voters

You can use Bayesian estimates to calculate weighted voting.

IMDB （互联网电影数据库）使用此计算，以确定其IMDB前250的（注：IMDB使用了10颗，但该公式是相同的使用5星）。的

IMDb (Internet Movie Database) uses this calculation to determine its IMDb Top 250. (Note: IMDb uses 10 stars but the formulas are identical using 5 stars).

该公式计算评分最高250标题给人以真正的贝叶斯估计：

The formula for calculating the Top Rated 250 Titles gives a true Bayesian estimate:

加权评级（WR）=（V÷（V + M））×R +（M÷（V + M））×C

weighted rating (WR) = (v ÷ (v+m)) × R + (m ÷ (v+m)) × C

其中：

  在R =平均影片（平均）=（额定值）    V =票的电影数量=（票）    M =所需的最低票数列在250强（目前3000）    C =在整个报告中的平均投票（目前为6.9）    R = average for the movie (mean) = (Rating) v = number of votes for the movie = (votes) m = minimum votes required to be listed in the Top 250 (currently 3000) C = the mean vote across the whole report (currently 6.9)

IMDB参考

维基百科参考