Feature Relevance

FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration

Most existing feature selection methods are insufficient for analytic purposes as soon as high dimensional data or redundant sensor signals are dealt with since features can be selected due to spurious effects or correlations rather than causal …

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. Besides model accuracy, the interpretation of these models itself is of high …

Interpretation of Linear Classifiers by Means of Feature Relevance Bounds

Research on feature relevance and feature selection problems goes back several decades, but the importance of these areas continues to grow as more and more data becomes available, and machine learning methods are used to gain insight and interpret, …

Interpretation of Linear Classifiers by Means of Feature Relevance Bounds

Research on feature relevance and feature selection problems goes back several decades, but the importance of these areas continues to grow as more and more data becomes available, and machine learning methods are used to gain insight and interpret, …