mirror of https://github.com/Yomguithereal/fog.git
78 lines
1.7 KiB
Markdown
78 lines
1.7 KiB
Markdown
[](https://travis-ci.org/Yomguithereal/fog)
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# Fog
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A fuzzy matching/clustering library for Python.
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## Installation
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You can install `fog` with pip with the following command:
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```
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pip install fog
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```
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## Usage
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* [Metrics](#metrics)
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- [sparse_cosine_similarity](#sparse_cosine_similarity)
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- [jaccard_similarity](#jaccard_similarity)
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- [weighted_jaccard_similarity](#weighted_jaccard_similarity)
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### Metrics
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#### sparse_cosine_similarity
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Computes the cosine similarity of two sparse weighted sets. Those sets have to be represented as counters.
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```python
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from fog.metrics import sparse_cosine_similarity
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# Basic
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sparse_cosine_similarity({'apple': 34, 'pear': 3}, {'pear': 1, 'orange': 1})
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>>> ~0.062
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```
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*Arguments*
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* **A** *Counter*: first weighted set. Must be a dictionary mapping keys to weights.
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* **B** *Counter*: second weighted set. Muset be a dictionary mapping keys to weights.
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---
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#### jaccard_similarity
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Computes the Jaccard similarity of two arbitrary iterables.
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```python
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from fog.metrics import jaccard_similarity
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# Basic
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jaccard_similarity('context', 'contact')
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>>> ~0.571
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```
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*Arguments*
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* **A** *iterable*: first sequence to compare.
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* **B** *iterable*: second sequence to compare.
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---
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#### weighted_jaccard_similarity
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Computes the weighted Jaccard similarity of two weighted sets. Those sets have to be represented as counters.
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```python
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from fog.metrics import weighted_jaccard_similarity
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# Basic
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weighted_jaccard_similarity({'apple': 34, 'pear': 3}, {'pear': 1, 'orange': 1})
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>>> ~0.026
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```
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*Arguments*
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* **A** *Counter*: first weighted set. Must be a dictionary mapping keys to weights.
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* **B** *Counter*: second weighted set. Muset be a dictionary mapping keys to weights.
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