Explanipedia

Editorial for ADAC issue 2 of volume 18 (2024) Open

Maurizio Vichi, Andrea Cerioli, Hans A. Kestler, Akinori Okada, Claus Weihs · 2024

How real is the quantitative turn? Investigating statistics as the new normal in linguistics Open

Sarah Buschfeld, Sven Leuckert, Claus Weihs, Andreas Weilinghoff · 2024

Statistical approaches in linguistics seem to have gained in importance in recent times, especially in the field of Corpus Linguistics. In particular, the last ten years have seen an upsurge of linguists being dedicated to statistical meth…

Editorial for ADAC issue 3 of volume 16 (2022) Open

Maurizio Vichi, Andrea Ceroli, Hans A. Kestler, Akinori Okada, Claus Weihs · 2022

Repeated undersampling in PrInDT (RePrInDT): Variation in undersampling and prediction, and ranking of predictors in ensembles Open

Claus Weihs, Sarah Buschfeld · 2021

In this paper, we extend our PrInDT method (Weihs & Buschfeld 2021a) towards undersampling with different percentages of the smaller and the larger classes (psmall and plarge), stratification of predictors, varying the prediction threshold…

Repeated undersampling in PrInDT (RePrInDT): Variation in undersampling\n and prediction, and ranking of predictors in ensembles Open

Claus Weihs, Sarah Buschfeld · 2021

In this paper, we extend our PrInDT method (Weihs & Buschfeld 2021a) towards\nundersampling with different percentages of the smaller and the larger classes\n(psmall and plarge), stratification of predictors, varying the prediction\nthresh…

Editorial for ADAC issue 2 of volume 15 (2021) Open

Maurizio Vichi, Andrea Cerioli, Hans A. Kestler, Akinori Okada, Claus Weihs · 2021

NesPrInDT: Nested undersampling in PrInDT Open

Claus Weihs, Sarah Buschfeld · 2021

In this paper, we extend our PrInDT method (Weihs, Buschfeld 2021) towards additional undersampling of one of the predictors. This helps us to handle multiple unbalanced data sets, i.e. data sets that are not only unbalanced with respect t…

Combining Prediction and Interpretation in Decision Trees (PrInDT) -- a Linguistic Example Open

Claus Weihs, Sarah Buschfeld · 2021

In this paper, we show that conditional inference trees and ensembles are suitable methods for modeling linguistic variation. As against earlier linguistic applications, however, we claim that their suitability is strongly increased if we …

Multi-Criteria Optimization in the Production of Lithium-Ion Batteries Open

Thomas Kornas, Dominik Wittmann, Rüdiger Daub, Oliver Meyer, Claus Weihs , et al. · 2020

Lithium-ion-batteries (LIBs) play a key role in determining the environmental impacts of future mobility technologies. In particular, the production of LIBs has a strong environmental impact as it is characterized by high scrap rates. In a…

Class Prediction by Prediction Intervals for Neural Nets Open

Claus Weihs, Malte Jastrow · 2020

Generally, the unknown coefficients of neural nets are estimated by nonlinear least squares. Therefore, prediction intervals for the true value of the target feature exist. The paper proposes to use such intervals for class prediction and …

Data Journalism – Impact of Statistical Methods Open

Claus Weihs, Marcel Pauly, Patrick Stotz · 2020

Data journalism strongly depends on adequate data preparation and analysis. In this paper, we discuss the impact of statistical methods on data journalistic analysis. To this end, we re-analyze two data journalistic publications of SPIEGEL…

Predicting industrial‐scale cell culture seed trains–A Bayesian framework for model fitting and parameter estimation, dealing with uncertainty in measurements and model parameters, applied to a nonlinear kinetic cell culture model, using an MCMC method Open

Tanja Hernández Rodríguez, C. Posch, Julia Schmutzhard, Josef Stettner, Claus Weihs , et al. · 2019

For production of biopharmaceuticals in suspension cell culture, seed trains are required to increase cell number from cell thawing up to production scale. Because cultivation conditions during the seed train have a significant impact on c…

Infill Criterion for Multimodal Model-Based Optimisation Open

Dirk Surmann, Uwe Ligges, Claus Weihs · 2018

Physical systems are modelled and investigated within simulation software in an increasing range of applications. In reality an investigation of the system is often performed by empirical test scenarios which are related to typical situati…

Arbeitszeiten von Professorinnen und Professoren in Deutschland 2016 Open

Claus Weihs, Tanja Hernández Rodríguez, Maximilian Doeckel, Christoph Marty, Holger Wormer · 2018

Data Science: the impact of statistics Open

Claus Weihs, Katja Ickstadt · 2018

In this paper, we substantiate our premise that statistics is one of the most important disciplines to provide tools and methods to find structure in and to give deeper insight into data, and the most important discipline to analyze and qu…

Classification Method Performance in High Dimensions Open

Claus Weihs, Tobias Kassner · 2018

We discuss standard classification methods for high-dimensional data and a small number of observations. By means of designed simulations illustrating the practical relevance of theoretical results we show that in the 2-class case the foll…

DMAIC in Lithium-Ion-Battery Production Open

Claus Weihs, Oliver Meyer, Sarah Schnackenberg · 2018

DMAIC refers to a data-driven cycle of analysis steps used for improving, optimizing and stabilizing business processes with the steps Define, Measure, Analyze, Improve, and Control (DMAIC). In this paper, we will demonstrate the Define, M…

Support Vector Machines for Survival Analysis with R Open

J. Césaire, R. König Inke, Claus Weihs, Andreas Ziegler, Marvin N. Wright · 2018

This article introduces the R package survivalsvm, implementing support vector machines for survival analysis. Three approaches are available in the package: The regression approach takes censoring into account when formulating the inequal…

Cutting Optimal Sections from Production Foils Open

Michael Kirchhof, Oliver Meyer, Stefan Mähr, Wolfgang Braunwarth, Claus Weihs · 2018

Rechargeable Lithium-Ion battery cell production is one of the most important processes in the field of electro mobility. The batteries’ electrodes are produced in the form of long coated foils which are then cut into pieces of a predefine…

Industrial Data Science: Developing a Qualification Concept for Machine Learning in Industrial Production Open

Nadja Bauer, Lukas Stankiewicz, Malte Jastrow, Daniel B. Horn, Jens Teubner , et al. · 2018

The advent of Industry 4.0 and the availability of large data storage systems lead to an increasing demand for specially educated data-oriented professionals in industrial production. The education of these specialists should combine eleme…

Online Linear Discriminant Analysis for Data Streams with Concept Drift Open

Sarah Schnackenberg, Uwe Ligges, Claus Weihs · 2018

Various methods based on classical classification methods such as linear discriminant analysis (LDA) have been developed for working on data streams in situations with concept drift. Nevertheless, the updated classifiers of such methods ma…

Combination of Several Control Charts Based on Dynamic Ensemble Methods Open

Dhouha Mejri, Mohamed Limam, Claus Weihs · 2017

Combining methods from Statistical ProcessControl (SPC) in order to benefit from more than one method's efficiency has been recently challenged.One of the reasons is that real life problems change overtime and a small improvement can lead …

Predicting measurements at unobserved locations in an electrical transmission system Open

Dirk Surmann, Uwe Ligges, Claus Weihs · 2017

A computational study of auditory models in music recognition tasks for normal-hearing and hearing-impaired listeners Open

Klaus Friedrichs, Nadja Bauer, Rainer Martin, Claus Weihs · 2017

Efficient Global Optimization: Motivation, Variations, and Applications Open

Claus Weihs, Swetlana Herbrandt, Nadja Bauer, Klaus Friedrichs, Daniel Horn · 2017

A popular optimization method of a black box objective function is Efficient Global Optimization (EGO), also known as Sequential Model Based Optimization, SMBO, with kriging and expected improvement. EGO is a sequential design of experimen…

Multi-objective selection of algorithm portfolios Open

Daniel Horn, Bernd Bischl, Aydın Demircioğlu, Tobias Glasmachers, Tobias Wagner , et al. · 2017

We propose a method for selecting a portfolio of algorithms optimizing multiple criteria. We select a portfolio of limited size and at the same time good quality from a possibly large pool of algorithms. Our method also helps to decide whi…

Model based optimization of a statistical simulation model for single diamond grinding Open

Swetlana Herbrandt, Uwe Ligges, Manuel Ferreira, Michael Kansteiner, Dirk Biermann , et al. · 2016

Fast model selection by limiting SVM training times Open

Aydın Demircioğlu, Daniel Horn, Tobias Glasmachers, Bernd Bischl, Claus Weihs · 2016

Kernelized Support Vector Machines (SVMs) are among the best performing supervised learning methods. But for optimal predictive performance, time-consuming parameter tuning is crucial, which impedes application. To tackle this problem, the…

Time efficient optimization of instance based problems with application to tone onset detection Open

Nadja Bauer, Klaus Friedrichs, Claus Weihs · 2016

A time efficient optimization technique for instance based problems is proposed, where for each parameter setting the target function has to be evaluated on a large set of problem instances. Computational time is reduced by beginning with …

A multivariate approach for onset detection using supervised classification Open

Nadja Bauer, Klaus Friedrichs, Claus Weihs · 2016

In this paper we introduce a new onset detection approach which incorporates a supervised classification model for estimating the tone onset probability in signal frames. In contrast to the most classical strategies where only one detectio…

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