mirror of https://github.com/explosion/spaCy.git
22 lines
1018 B
Plaintext
22 lines
1018 B
Plaintext
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//- 💫 DOCS > API > TEXTCATEGORIZER
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include ../../_includes/_mixins
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p
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| Add text categorization models to spaCy pipelines. The model supports
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| classification with multiple, non-mutually exclusive labels.
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p
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| You can change the model architecture rather easily, but by default, the
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| #[code TextCategorizer] class uses a convolutional neural network to
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| assign position-sensitive vectors to each word in the document. This step
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| is similar to the #[+api("tensorizer") #[code Tensorizer]] component, but the
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| #[code TextCategorizer] uses its own CNN model, to avoid sharing weights
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| with the other pipeline components. The document tensor is then
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| summarized by concatenating max and mean pooling, and a multilayer
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| perceptron is used to predict an output vector of length #[code nr_class],
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| before a logistic activation is applied elementwise. The value of each
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| output neuron is the probability that some class is present.
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+under-construction
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