ltfmselector 2.0.2

Locally-Tailored Feature and Model Selector with Deep Q-Learning

LTFMSelector: Locally-Tailored Dynamic Feature and Model Selector with Deep Reinforcement Learning

Installation

pip install ltfmselector

Basic usage

from ltfmselector import LTFMSelector

# Initialize an agent to learn to selects features and models, specifically tailored to each example
AgentSelector = LTFMSelector(<#episodes>, pType=<'classification', 'regression'>)

# Fit
AgentSelector(<X: pd.DataFrame>, <y: pd.Series>)

# Predict
y_pred, doc = AgentSelector.predict(<X_test: pd.DataFrame>)

For more examples check out the examples.

Citing LTFMSelector

This library is implemented based on the work presented in this abstract:

J.C. Liaw, C.Z. Chaing, D. Raab, M. Siebler, H. Hefter, D. Zietz, M. Jäger, A. Kecskeméthy, F. Geu Flores. Interdisciplinary Gait Assessment with Patient-Specific Feature and Model Selection via Reinforcement Learning. 11. IFToMM D-A-CH Konferenz 2025, 20./21. Februar 2025, FH Kärnten, Villach. HTML