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The IMDb Movie Reviews dataset is a binary sentiment analysis dataset consisting of 50,000 reviews from the Internet Movie Database (IMDb) labeled as positive or negative. The dataset contains an even number of positive and negative reviews. Only highly polarizing reviews are considered.
This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training and 25,000 for testing.
- Imdb_Reviews/Plain_Text
- Imdb_Reviews/Bytes
- Imdb_Reviews/Subwords8k
- Imdb_Reviews/Subwords32k
Config description: Plain textDataset size: 129.83 MiBFeature structure:Config description: Uses byte-level text encoding withtfds.deprecated.text.ByteTextEncoderDataset size: 129.88 MiBFeature structure:Config description: Uses tfds.deprecated.text.SubwordTextEncoderwith8k vocab sizeDataset size: 54.72 MiBFeature structure:Config description: Uses tfds.deprecated.text.SubwordTextEncoderwith32k vocab sizeDataset size: 50.33 MiBFeature structure:The dataset files can be accessed and downloaded from https://datasets.imdbws.com/. The data is refreshed daily. IMDb Dataset Details. Each dataset is contained in a gzipped, tab-separated-values (TSV) formatted file in the UTF-8 character set. The first line in each file contains headers that describe what is in each column.
Refresh. Large Movie Review Dataset.
Aug 2, 2020 · This dataset contains nearly 1 Million unique movie reviews from 1150 different IMDb movies spread across 17 IMDb genres - Action, Adventure, Animation, Biography, Comedy, Crime, Drama, Fantasy, History, Horror, Music, Mystery, Romance, Sci-Fi, Sport, Thriller and War.
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What is the IMDb movie reviews dataset?
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IMDB Movie Reviews Large Dataset - 50k Reviews. This dataset is taken from https://ai.stanford.edu/~amaas/data/sentiment/ and then preprocess to put all positive and negative reviews in the same file for training and testing. It help you to put more effort on algorithm instead of data collection.
