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README.md
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### Dataset Summary
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This dataset is an adapted version of "IMDb Movie Dataset: All Movies by Genre" found at: https://www.kaggle.com/datasets/rajugc/imdb-movies-dataset-based-on-genre?select=history.csv.
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Within the dataset, the movie title and year columns were combined, the genre was extracted from the seperate csv files, the pre-existing genre column was renamed to expanded-genres, any movies missing a description (i.e. the description was written as "Add a plot") were dropped from the original data, the rating column was left the same, and finally the rest of the remaining columns were dropped.
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The columns in the data are: "movie title - year", "genre", "expanded-genres", "rating", and "description"
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### Data Instances
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imdb_genres = 300388 entries
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training = 240310 entries
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test = 30039 entries
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validation = 30039 entries
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An example of an entries looks as follows:
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{
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"movie title - year" : "Die Hard - 1988",
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"genre" : "Action",
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"rating" : 8.2,
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"description" : "A New York City police officer tries to save his estranged wife and several others taken hostage by terrorists during a Christmas party at the Nakatomi Plaza in Los Angeles."
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}
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### Data Fields
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The data fields are the same among all splits.
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Fields are as follows:
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## Dataset Creation
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### Dataset Summary
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This dataset is an adapted version of **"IMDb Movie Dataset: All Movies by Genre"** found at: https://www.kaggle.com/datasets/rajugc/imdb-movies-dataset-based-on-genre?select=history.csv.
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Within the dataset, the movie title and year columns were combined, the genre was extracted from the seperate csv files, the pre-existing genre column was renamed to expanded-genres, any movies missing a description (i.e. the description was written as "Add a plot") were dropped from the original data, the rating column was left the same, and finally the rest of the remaining columns were dropped.
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The columns in the data are: "movie title - year", "genre", "expanded-genres", "rating", and "description"
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### Data Instances
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**imdb_genres** = 300388 entries
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- Total amount of disk used: 68.0 MB
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**training** = 240310 entries
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- Total amount of disk used: 54.4 MB
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**test** = 30039 entries
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- Total amount of disk used: 6.8 MB
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**validation** = 30039 entries
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- Total amount of disk used: 6.8 MB
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An example of an entries looks as follows:
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```
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{
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"movie title - year" : "Die Hard - 1988",
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"genre" : "Action",
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"rating" : 8.2,
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"description" : "A New York City police officer tries to save his estranged wife and several others taken hostage by terrorists during a Christmas party at the Nakatomi Plaza in Los Angeles."
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}
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```
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### Data Fields
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The data fields are the same among all splits.
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Fields are as follows:
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- "movie title - year": a string feature.
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- "genre": a string classification label, with the possible values: 'Adventure', 'Action', 'Thriller', 'Romance', 'Crime', 'Fantasy', 'Mystery', 'Horror', 'War', 'Family', 'Animation', 'Scifi', 'Sports', 'History', 'Biography', and 'Film-noir'.
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- "expanded-genres" : a string feature.
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- "rating" : a floating point value, ranging from 0.0 to 10.0.
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- "description" : a string feature.
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## Dataset Creation
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