Char Classifier
---------
Given a short phrase, train a neural network to classify it based on the characters that it contains.
The trainer takes in a file of phrases (separated by new line) and a file of target values (separated by new line).
To train on the sample data (parts of speech classification):
```
from phrase_classifier import PhraseClassificationTrainer, PhraseClassifier
p = PhraseClassificationTrainer("sample/words", "sample/parts-of-speech")
p.train([100, 100], 20, 100)
p.save("sample", "example-run")
```
This will save a trained model with the tag 'example-run' in the sample directory. To use that model, run:
```
k = PhraseClassifier("sample", "example-run")
print k.classify("dog")
```
---------
Given a short phrase, train a neural network to classify it based on the characters that it contains.
The trainer takes in a file of phrases (separated by new line) and a file of target values (separated by new line).
To train on the sample data (parts of speech classification):
```
from phrase_classifier import PhraseClassificationTrainer, PhraseClassifier
p = PhraseClassificationTrainer("sample/words", "sample/parts-of-speech")
p.train([100, 100], 20, 100)
p.save("sample", "example-run")
```
This will save a trained model with the tag 'example-run' in the sample directory. To use that model, run:
```
k = PhraseClassifier("sample", "example-run")
print k.classify("dog")
```
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Metadata
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Release files for chClassifier 0.6.0
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|---|---|---|---|---|
| chClassifier-0.6.0-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 12.1 kB
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