基于贝叶斯分类模型的电影票房预测研究

Research on the Prediction of Film Box Office Based on Bayesian Classification Model

贝叶斯分类属于概率统计知识中的一种分类算法,具有高精度、高效率等特点。它根据某对象的先验概率,利用贝叶斯公式计算出其后验概率,选择具有最大后验概率的类作为该对象所属的类。文章基于贝叶斯模型理论对2018年上映的45部电影票房进行研究,通过测试其中15部电影票房测试样本,准确率达到80%,并从中挖掘出影响电影票房的重要因素,为预测电影票房提供一定的科学的依据。

Bayesian classification is a classification algorithm in probability statistics knowledge,which has the characteristics of high accuracy and high efficiency.According to the prior probability of an object,it calculates its posterior probability by Bayesian formula,and chooses the class with the maximum posterior probability as the class to which the object belongs.Based on the Bayesian model theory,the box offices of 45 films released in 2018 are studied.Through testing 15 film box offices,the accuracy rate reaches 80%.It also excavates the important factors affecting the box office and provides a scientific basis for prediction.