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			20 lines
		
	
	
		
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			20 lines
		
	
	
		
			1023 B
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
//- 💫 DOCS > API > TEXTCATEGORIZER
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include ../_includes/_mixins
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p
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    |  The model supports classification with multiple, non-mutually exclusive
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    |  labels. You can change the model architecture rather easily, but by
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    |  default, the #[code TextCategorizer] class uses a convolutional
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    |  neural network to assign position-sensitive vectors to each word in the
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    |  document. The #[code TextCategorizer] uses its own CNN model, to
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    |  avoid sharing weights with the other pipeline components. The document
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    |  tensor is then summarized by concatenating max and mean pooling, and a
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    |  multilayer perceptron is used to predict an output vector of length
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    |  #[code nr_class], before a logistic activation is applied elementwise.
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    |  The value of each output neuron is the probability that some class is
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    |  present.
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//- This class inherits from Pipe, so this page uses the template in pipe.jade.
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!=partial("pipe", { subclass: "TextCategorizer", short: "textcat", pipeline_id: "textcat" })
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