Initialize trues to 0.0 in training example (#3004)

* added contributor agreement

* if there are no true positives, precision should be 0.0
This commit is contained in:
Gavriel Loria 2018-12-02 19:33:22 -05:00 committed by Matthew Honnibal
parent 33fca8672f
commit ae5601beae
2 changed files with 108 additions and 2 deletions

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.github/contributors/gavrieltal.md vendored Normal file
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# spaCy contributor agreement
This spaCy Contributor Agreement (**"SCA"**) is based on the
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The SCA applies to any contribution that you make to any product or project
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Read this agreement carefully before signing. These terms and conditions
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## Contributor Agreement
1. The term "contribution" or "contributed materials" means any source code,
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## Contributor Details
| Field | Entry |
|------------------------------- | -------------------- |
| Name | Gavriel Loria |
| Company name (if applicable) | |
| Title or role (if applicable) | |
| Date | Nov 29, 2018 |
| GitHub username | gavrieltal |
| Website (optional) | |

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@ -106,10 +106,10 @@ def load_data(limit=0, split=0.8):
def evaluate(tokenizer, textcat, texts, cats): def evaluate(tokenizer, textcat, texts, cats):
docs = (tokenizer(text) for text in texts) docs = (tokenizer(text) for text in texts)
tp = 1e-8 # True positives tp = 0.0 # True positives
fp = 1e-8 # False positives fp = 1e-8 # False positives
fn = 1e-8 # False negatives fn = 1e-8 # False negatives
tn = 1e-8 # True negatives tn = 0.0 # True negatives
for i, doc in enumerate(textcat.pipe(docs)): for i, doc in enumerate(textcat.pipe(docs)):
gold = cats[i] gold = cats[i]
for label, score in doc.cats.items(): for label, score in doc.cats.items():