Box Office Success Prediction Through Artificial Neural Network and Machine Learning Algorithm

Jay Bhatt, Saurav Verma
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引用次数: 1

Abstract

In this study, a comparison is made between Artificial Neural Network Algorithm and Machine Learning Algorithm of Support Vector Machine by considering pre-release and pre plus post release features of a movie for predicting a movie to a particular success class. These success classes includes Flop/Disaster, Average, Hit, Super-Hit and Block-Buster of a movie. Our best performing model from Artificial Neural Network and Support Vector Machine is able to give better performance in order to predict any particular movie to specific success class of a movie for both the cases of prerelease as well as pre plus post release features of a movie.
基于人工神经网络和机器学习算法的票房成功预测
在本研究中,通过考虑电影上映前和上映前后的特征,将人工神经网络算法与支持向量机的机器学习算法进行比较,以预测电影的特定成功类别。这些成功类别包括电影的失败/灾难、一般、成功、超级成功和大片。我们最好的人工神经网络和支持向量机模型能够提供更好的性能,以预测任何特定电影的特定成功类别,无论是在电影的预发行情况下,还是在电影的预发行和后发行特征上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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