Registry / ai-ml / pyhacrf-datamade

pyhacrf-datamade

library0.2.8pypypi✓ verified 82d ago

Hidden alignment conditional random field (HACRF) for discriminative string edit distance. Current version 0.2.8, infrequent releases.

ai-ml data

pip install pyhacrf-datamade

github ↗package ↗

INSTALL

IMPORT

SIG · PYHACRF-DATAMADE

pyhacrf-datamade

ai-mlpythonv0.2.8

harness data pending

Install & Compatibility

Where this runs

No compatibility data collected yet for this library.

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Hacrf

✓ from pyhacrf import Hacrf

✗ from pyhacrf import HACRF

PairFeatureExtractor

✓ from pyhacrf import PairFeatureExtractor

StringPairFeatureExtractor

✓ from pyhacrf import StringPairFeatureExtractor

Minimal example: train HACRF on string pairs and predict.

from pyhacrf import HACRF import numpy as np # Example strings as lists of characters X = [list('abc'), list('abd'), list('abce')] y = [0, 0, 1] model = HACRF() model.fit(X, y) predictions = model.predict([list('abe')]) print(predictions)

Debug

Known issues

gotchaInput strings must be passed as lists of characters (or tokens), not as raw strings. For example, pass ['a','b','c'] not 'abc'.

fix

Convert strings to list: list('abc')

affects: all

deprecatedThe version 0.2.6 changed the API: previously used 'model.fit(X, y, ...)' now requires explicit 'model.fit(X, y)'. Some older examples show deprecated arguments like 'verbose'.

fix

Remove deprecated arguments; update to current fit signature.

affects: <0.2.6

gotchaThe HACRF model expects X to be a list of string pairs? Actually, the input X is a list of strings (each string to align). For pairwise alignment, you need to construct paired examples yourself.

fix

For pairwise edit distance, pass two lists: X = list(zip(strings1, strings2)), then model.fit(X, y). But ensure each element is a list of characters.

affects: all

breakingWhen upgrading from 0.2.4 to 0.2.6, the internal Cython alignment structure changed; models saved with older versions may not load.

fix

Retrain models after upgrading.

affects: <0.2.6

Upgrade

Version history

0.2.8latest on PyPI · released Jun 20, 2024

Audit

Dependencies

numpyrequiredCore dependency for array operations

scipyrequiredUsed for optimization (L-BFGS-B)

sklearnoptionalOptional for metrics and cross-validation

Agent activity

10 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/datamade/pyhacrf ↗

packagehttps://pypi.org/project/pyhacrf-datamade/ ↗