CosineSimilarityClassifier

class squirro.lib.nlp.steps.classifiers.CosineSimilarityClassifier(config)

Bases: squirro.lib.nlp.steps.classifiers.Classifier

The cosine similarity Classifier uses the cosine similarity to decide which text fragment is closest to which class.

Input - the input field need to be of type list [ float or int ] or numpy.ndarray

Output - the output field is filled with data of type dict { str : float }. The key of the dict is the predicted class name and the value is the cosine distance to the closest reference data point.

Parameters

type (str) – cosine_similarity

Example

{
    "step": "classifier",
    "type": "cosine_similarity",
    "label_field": "label",
    "input_field": "embedded_extract",
    "output_field": "prediction",
}

Methods Summary

load()	Load a step
process(docs)	Process a set of documents
process_batch(batch)	Process a batch of documents.
save()	Save a step
train(docs)	Train on a step of a set of documents

Methods Documentation

load()

Load a step

process(docs)

Process a set of documents

Parameters

docs (generator(Document)) – Generator of documents

Returns

Generator of processed documents

Return type

generator(Document)

process_batch(batch)

Process a batch of documents. If not defined will default to using self.process_doc for each document in the batch.

Parameters

batch (list(Document)) – List of documents

Returns

List of processed documents

Return type

list(Document)

save()

Save a step

train(docs)

Train on a step of a set of documents

Parameters

docs (generator(Document)) – Generator of documents

Returns

Generator of processed documents

Return type

generator(Document)