Employability of the Data Analysis of the Relevant Dataset Based on Classification and Clustering Algorithms in the Effective Prediction of Movies

Saniya Malik

Volume 4, Issue 1 2020

Page: 44-48

Abstract

In Movie Analysis, Big Data enables us to evaluate the model more precisely and eliminate process-associated speculation. The main purpose of this research is to investigate and produce training data that can predict the movie's earnings. We used the data from Kaggle, which included information on 3,000 films, including the title, cast, and budget. The collection is evaluated, visualized, and trained with the help of two classification techniques in this project. The two methods are Regularization and Strange Wooded. The algorithm withthe lowest score is chosen after being evaluated using its RMSE values. Our most recent prediction was for a movie in the collection that didn't bring in any money.

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References

  • Early Prediction of movie Box-Office success. Based on Wikipedia Activity Big Data.Marton Mestyan, Taha Yasseri, Janos Kertesz, 2012.
  • Sentiment Analysis of Movie Reviews using Machine Learning Techniques. Palak Baid,Apoorva Gupta, Neelam chaplot, 2017.
  • Movie Success Prediction using Data Mining. Anantharaman V, Ebin G. Job, Neha sam,Sheryl Maria Sebastian, 2019.

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