Empulse

Empulse is a package aimed to enable value-driven analysis in Python. The package implements popular value-driven metrics and algorithms in accordance to sci-kit learn conventions. This allows the measures to seamlessly integrate into existing ML workflows.

Installation

Install empulse via pip with

pip install empulse

Documentation

You can find the documentation here.

Usage

We offer custom metrics and models. You can use them within the scikit-learn ecosystem.

# the scikit learn stuff we love
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline
from sklearn.datasets import make_classification
from sklearn.model_selection import cross_val_score
from sklearn.metrics import make_scorer

# the stuff we add
from empulse.metrics import empc_score
from empulse.models import ProfLogitClassifier

X, y = make_classification()

pipeline = Pipeline([
    ("scale", StandardScaler()),
    ("model", ProfLogitClassifier())
])

cross_val_score(pipeline, X, y, scoring=make_scorer(empc_score, needs_proba=True))