main webpage W Topic Feature Selection TUbilio (Technical University of Darmstadt) The Terminating-Random Experiments Selector: Fast High-Dimensional Variable Selection with False Discovery Rate Control 2021 We propose the Terminating-Random Experiments (T-Rex) selector, a fast variable selection method for high-dimensional data. The T-Rex selector controls a user-defined target false discovery rate (FDR) while maximizing the number of selected variables. This is… Article Open Feature Selection Open Article Page

Feature Selection

Procedure in machine learning and statistics Feature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Stylometry and DNA microarray analysis are two cases where feature selection is used. It should be distinguished from feature extraction. Feature selection techniques are used for several reasons: simplification of models to make them easier to interpret by researchers/users, shorter training times, to avoid the curse of dimensionality, improve data's compatibility with a learning model class, encode inherent symmetries present in the input space. Critical Symbolic Virtual Narrative Open Feature Selection Open Article Page

Exploring foci of: TUbilio (Technical University of Darmstadt) The Terminating-Random Experiments Selector: Fast High-Dimensional Variable Selection with False Discovery Rate Control 2021 We propose the Terminating-Random Experiments (T-Rex) selector, a fast variable selection method for high-dimensional data. The T-Rex selector controls a user-defined target false discovery rate (FDR) while maximizing the number of selected variables. This is achieved by fusing the solutions of multiple early terminated random experiments. The experiments are conducted on a combination of the original predictors and multiple sets of randomly generated dummy predictors. A finite sample proof based on martingale the… Open Article Page

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Explore Feature Selection W Topic Feature Selection TUbilio (Technical University of Darmstadt) The Terminating-Random Experiments Selector: Fast High-Dimensional Variable Selection with False Discovery Rate Control 2021 We propose the Terminating-Random Experiments (T-Rex) selector, a fast variable selection method for high-dimensional data. The T-Rex selector controls a user-defined target false discovery rate (FDR) while maximizing the number of selected variables. This is… Article Critical Symbolic Virtual Narrative Open Feature Selection Open Article Page