Search Results for author:
Found 4 papers, 3 papers with code
SAM-kNN Regressor for Online Learning in Water Distribution Networks
In this work, we propose an adaption of the incremental SAM-kNN classifier for regression to build a residual based anomaly detection system for water distribution networks that is able to adapt to any kind of change.
Analysis of Drifting Features
The notion of concept drift refers to the phenomenon that the distribution, which is underlying the observed data, changes over time.
Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information
In this contribution, we focus on feature selection paradigms, which enable us to uncover relevant factors of a given regularity based on a sparse model.
Feature Relevance Bounds for Ordinal Regression
The increasing occurrence of ordinal data, mainly sociodemographic, led to a renewed research interest in ordinal regression, i. e. the prediction of ordered classes.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
