spaCy/website/api/textcategorizer.jade
2017-11-01 19:49:04 +01:00

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//- 💫 DOCS > API > TEXTCATEGORIZER
include ../_includes/_mixins
p
| The model supports classification with multiple, non-mutually exclusive
| labels. You can change the model architecture rather easily, but by
| default, the #[code TextCategorizer] class uses a convolutional
| neural network to assign position-sensitive vectors to each word in the
| document. The #[code TextCategorizer] uses its own CNN model, to
| avoid sharing weights with the other pipeline components. The document
| tensor is then summarized by concatenating max and mean pooling, and a
| multilayer perceptron is used to predict an output vector of length
| #[code nr_class], before a logistic activation is applied elementwise.
| The value of each output neuron is the probability that some class is
| present.
//- This class inherits from Pipe, so this page uses the template in pipe.jade.
!=partial("pipe", { subclass: "TextCategorizer", short: "textcat", pipeline_id: "textcat" })