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.
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