Benjamin Schowe und Feature Selection - Info zur Person

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Workshop IR - LWA Lernen, …

www.kde.cs.uni-kassel.de

KDML: Benjamin Schowe & Katharina Morik: Fast-Ensembles of Minimum Redundancy Feature Selection; KDML: Weiwei Cheng, Krzysztof Dembczynski & Eyke Hüllermeier: Graded Multilabel Classification: The Ordinal Case; JOINT6 ABIS+IR: 14: :30

Gladiator

kobra.uni-kassel.de

Stefan Rueping. Fast-Ensembles of Minimum Redundancy Feature Selection : : : : : : : : : : : : : : : : 137 Benjamin Schowe and Katharina Morik.

RapidMiner Feature Selection Extension / Wiki / Home

sourceforge.net

Authors: Benjamin Schowe. This RapidMiner-plugin consists of operators for feature selection and classification - mainly on high-dimensional (microarray-) data ...

Ensembles in Machine Learning Applications - Google Books

books.google.com.sv

Benjamin Schowe and Katharina Morik Abstract. Finding relevant subspaces in very high-dimensional data is a challenging task not only for microarray data. The selection of features is to enhance the classification performance, but on the other hand the feature selection must be stable, i.e., the set of features selected ...

Automated System for Drilling Operations Classification ...Montanuniversität Leoben

pure.unileoben.ac.at

von B Esmael · · Zitiert von: 9 — [5] Benjamin Schowe, “Feature Selection for high-dimensional data with RapidMiner“, Technical University of Dortmund,

LWA 2010: Kassel, GermanyUni Trier

dblp1.uni-trier.de

Benjamin Schowe, Katharina Morik: Fast-Ensembles of Minimum Redundancy Feature Selection.

dblp: Fast-Ensembles of Minimum Redundancy Feature Selection.

dblp.dagstuhl.de

Bibliographic details on Fast-Ensembles of Minimum Redundancy Feature Selection.

Feature Selection for high-dimensional data with RapidMinerTU Dortmund

kissen.cs.uni-dortmund.de

von B Schowe · Zitiert von: 34 — Benjamin Schowe. Technical University of Dortmund. Artificial Intelligence Group . Abstract.

Fast-Ensembles of Minimum Redundancy Feature Selection | SpringerLink

link.springer.com

Finding relevant subspaces in very high-dimensional data is a challenging task not only for microarray data. The selection of features is to enhance the...

Data Mining on Ice | SpringerLink

link.springer.com

In an atmospheric neutrino analysis for IceCube’s 59-string configuration, the impact of detailed feature selection on the performance of machine learning...

Combining forward selection and backward eliminationRapidMiner

community.rapidminer.com

— Maybe the new feature selection extension of Benjamin Schowe might be interesting for you? He will present it at the RCOMM in Dublin this ...

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Benjamin Schowe und Feature Selection Person-Info