Bag of tricks for efficient text classification
Proceedings of the 15th conference of the European chapter of the�…, 2017•aclanthology.org
This paper explores a simple and efficient baseline for text classification. Our experiments
show that our fast text classifier fastText is often on par with deep learning classifiers in terms
of accuracy, and many orders of magnitude faster for training and evaluation. We can train
fastText on more than one billion words in less than ten minutes using a standard multicore
CPU, and classify half a million sentences among 312K classes in less than a minute.
show that our fast text classifier fastText is often on par with deep learning classifiers in terms
of accuracy, and many orders of magnitude faster for training and evaluation. We can train
fastText on more than one billion words in less than ten minutes using a standard multicore
CPU, and classify half a million sentences among 312K classes in less than a minute.
Abstract
This paper explores a simple and efficient baseline for text classification. Our experiments show that our fast text classifier fastText is often on par with deep learning classifiers in terms of accuracy, and many orders of magnitude faster for training and evaluation. We can train fastText on more than one billion words in less than ten minutes using a standard multicore CPU, and classify half a million sentences among 312K classes in less than a minute.
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