Abstract:
In present world, machine learning techniques and models are used to predict future.
Prediction the movie success before its release has been an immense point of concern for
movie industry related all people, especially producer, shake holders and director. Since
Bangladeshi movie industry is in threat, they need some kind of assurance that the movie
will be successful or not and which factor can improve the profit. The purpose of the work
is to make a model which predict Bangla movie success depending on some pre-release
factors like actor, actress, director, producer, genre, budget, release date, duration, playback
singer, music director that helps Bangladeshi movie industry to determinate specific reason
for success so that they can resolve before release.
In this model, data mining process and algorithm are applied for movie classification.
Decision tree, Random forest, Logistic Regression, Support Vector machine are used and
evaluated on this dataset and also focus on to find out some interesting relationship between
features using feature engineering techniques and tools. Here, it is supervised classification
which classify movie based on IMdb movie rating, where rating are divided into five
classes (flop, bad, watchable, super hit and block buster). I visited all Bangladeshi movie
related sites to collect data. As Bangladeshi movie data collection is highly unorganized
and unavailable, our dataset is not much more longer. This prototype model has been
provided much better performance in this challenging scenario.
