pyecoacc 1.0.0

A python package for supervised learning of behavioral modes from sensor data.

pyecoacc

A python package for supervised learning of behavioral modes from sensor data.

pyecoacc is built on top of sklearn and pytorch, and provides convenient pipelines of feature computations and other preprocessing necessary to easily run behavior classification on sensor data. This package contains easy to use out of the box optoins, together with extendability and customization.

📦 Installation

Install from PyPI:

pip install pyecoacc   

Or from the source:

git clone https://github.com/Hezi-Resheff/pyecoacc.git
cd pyecoacc
pip install .

🔗 Dependencies

All required dependencies are listed in requirements.txt. To install them manually:

pip install -r requirements.txt

🧑‍💻 Usage

from pyecoacc.models.pipeline import get_default_random_forest_pipeline

classifier = get_default_random_forest_pipeline()
classifier.fit(ACC_train, y_train)
y_hat = classifier.predict(ACC_test)