Welcome to DistClassiPy’s documentation!

Welcome to DistClassiPy’s documentation!#

DistClassiPy is a Python package for a distance-based classifier which can use several different distance metrics.

Installation#

To install DistClassiPy, run the following command:

pip install distclassipy

Usage#

Here’s a quick example to get you started with DistClassiPy:

import distclassipy as dcpy
from sklearn.datasets import make_classification

X, y = make_classification(
    n_samples=1000,
    n_features=4,
    n_informative=2,
    n_redundant=0,
    random_state=0,
    shuffle=False,
)
clf = dcpy.DistanceMetricClassifier(metric="canberra")
clf.fit(X, y)
print(clf.predict([[0, 0, 0, 0]]))

Features#

  • Multiple distance metrics support

  • Easy integration with existing data processing pipelines

  • Efficient and scalable for large datasets

Authors#

Siddharth Chaini, Ashish Mahabal, Ajit Kembhavi and Federica B. Bianco.

Indices and tables#

API Documentation#

API Reference

Contents