33 citations · 61 across the 8 of their papers we have counts for
5 papers · 1 filter
Towards Understanding the Survival of Patients with High-Grade Gastroenteropancreatic Neuroendocrine Neoplasms: An Investigation of Ensemble Feature Selection in the Prediction of Overall Survival
Anna Jenul, Henning Langen Stokmo, Stefan Schrunner +3
Determining the most informative features for predicting the overall survival of patients diagnosed with high-grade gastroenteropancreatic neuroendocrine neoplasms is crucial to im…
Ranking Feature-Block Importance in Artificial Multiblock Neural Networks
Anna Jenul, Stefan Schrunner, Bao Ngoc Huynh +4
In artificial neural networks, understanding the contributions of input features on the prediction fosters model explainability and delivers relevant information about the dataset.…
A User-Guided Bayesian Framework for Ensemble Feature Selection in Life Science Applications (UBayFS)
Anna Jenul, Stefan Schrunner, Jürgen Pilz +1
Feature selection represents a measure to reduce the complexity of high-dimensional datasets and gain insights into the systematic variation in the data. This aspect is of specific…
Towards a General Framework to Embed Advanced Machine Learning in Process Control Systems
Stefan Schrunner, Michael Scheiber, Anna Jenul +3
Since high data volume and complex data formats delivered in modern high-end production environments go beyond the scope of classical process control systems, more advanced tools i…
RENT -- Repeated Elastic Net Technique for Feature Selection
Anna Jenul, Stefan Schrunner, Kristian Hovde Liland +3
Feature selection is an essential step in data science pipelines to reduce the complexity associated with large datasets. While much research on this topic focuses on optimizing pr…