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A fuzzy matching & clustering library for python.
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README.md

Build Status

Fog

A fuzzy matching/clustering library for Python.

Installation

You can install fog with pip with the following command:

pip install fog

Usage

Metrics

sparse_cosine_similarity

Computes the cosine similarity of two sparse weighted sets. Those sets have to be represented as counters.

from fog.metrics import sparse_cosine_similarity

# Basic
sparse_cosine_similarity({'apple': 34, 'pear': 3}, {'pear': 1, 'orange': 1})
>>> ~0.062

Arguments

  • A Counter: first weighted set. Must be a dictionary mapping keys to weights.
  • B Counter: second weighted set. Muset be a dictionary mapping keys to weights.

jaccard_similarity

Computes the Jaccard similarity of two arbitrary iterables.

from fog.metrics import jaccard_similarity

# Basic
jaccard_similarity('context', 'contact')
>>> ~0.571

Arguments

  • A iterable: first sequence to compare.
  • B iterable: second sequence to compare.

weighted_jaccard_similarity

Computes the weighted Jaccard similarity of two weighted sets. Those sets have to be represented as counters.

from fog.metrics import weighted_jaccard_similarity

# Basic
weighted_jaccard_similarity({'apple': 34, 'pear': 3}, {'pear': 1, 'orange': 1})
>>> ~0.026

Arguments

  • A Counter: first weighted set. Must be a dictionary mapping keys to weights.
  • B Counter: second weighted set. Muset be a dictionary mapping keys to weights.