mirror of
				https://github.com/explosion/spaCy.git
				synced 2025-11-04 09:57:26 +03:00 
			
		
		
		
	
		
			
				
	
	
		
			22 lines
		
	
	
		
			1018 B
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
			
		
		
	
	
			22 lines
		
	
	
		
			1018 B
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
//- 💫 DOCS > API > TEXTCATEGORIZER
 | 
						|
 | 
						|
include ../../_includes/_mixins
 | 
						|
 | 
						|
p
 | 
						|
    |  Add text categorization models to spaCy pipelines. The model supports
 | 
						|
    |  classification with multiple, non-mutually exclusive labels.
 | 
						|
 | 
						|
p
 | 
						|
    |  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. This step
 | 
						|
    |  is similar to the #[+api("tensorizer") #[code Tensorizer]] component, but 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.
 | 
						|
 | 
						|
+under-construction
 |