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Found 6 papers, 3 papers with code
Towards Understanding the Survival of Patients with High-Grade Gastroenteropancreatic Neuroendocrine Neoplasms: An Investigation of Ensemble Feature Selection in the Prediction of Overall Survival
Determining the most informative features for predicting the overall survival of patients diagnosed with high-grade gastroenteropancreatic neuroendocrine neoplasms is crucial to improve individual treatment plans for patients, as well as the biological understanding of the disease.
Ranking Feature-Block Importance in Artificial Multiblock Neural Networks
This work presents three methods pursuing distinct strategies to rank features in multiblock ANNs by their importance: (1) a composite strategy building on individual feature importance rankings, (2) a knock-in, and (3) a knock-out strategy.
A User-Guided Bayesian Framework for Ensemble Feature Selection in Life Science Applications (UBayFS)
Feature selection represents a measure to reduce the complexity of high-dimensional datasets and gain insights into the systematic variation in the data.
Towards a General Framework to Embed Advanced Machine Learning in Process Control Systems
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 involving machine learning are required to reliably recognize failure patterns.
Principal component-based image segmentation: a new approach to outline in vitro cell colonies
Identification, segmentation and counting of stained colonies play a vital part in high-throughput screening and quantitative assessment of biological assays.
Cultural Vocal Bursts Intensity Prediction
Image Segmentation
+2
RENT -- Repeated Elastic Net Technique for Feature Selection
Furthermore, unlike established feature selectors, RENT provides valuable information for model interpretation concerning the identification of objects in the data that are difficult to predict during training.
