Skip to main content

Library for processing and visualizing behavioral biometric data

Project description

behalearn

behalearn is a library that simplifies data preparation and feature extraction for behavioral biometric data (such as mouse movements, touch movements, accelerometer data). Such data may be subsequently used for e.g. implicit user authenticaton.

behalearn also provides a handful of simple, interactive visualizations of raw data, pre-processed data and reports of prediction results (such as the DET curve).

Installation

The source code is currently hosted on GitLab.

The easiest way to install behalearn is via pip:

pip install behalearn

Usage

Simply import individual behalearn modules or their functions/classes, for example:

from behalearn.features import FeatureExtractor

The DEMO.ipynb file shows examples of basic behalearn usage.

Documentation

The official documentation and structure of the library is available here.

License

Source code is provided under the MIT License.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

behalearn-3.0.1.tar.gz (39.1 kB view hashes)

Uploaded Source

Built Distribution

behalearn-3.0.1-py3-none-any.whl (57.5 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page