RAISING Workflow
A visual representation of the RAISING workflow and its application in detecting genomic signatures of polygenic selection.
An automated supervised deep learning framework
A visual representation of the RAISING workflow and its application in detecting genomic signatures of polygenic selection.
RAISING: a two-stage supervised deep learning framework for hyperparameter tuning and feature selection. It contains two primary functions: hp_optimization and feature_importance. In the first stage, users perform hyperparameter tuning through the hp_optimization function and pass the optimal neural network (NN) architecture to feature_importance to train the architecture on the entire dataset and estimate the feature importance. Explore the documentation and tutorials for deeper insights.