NN Classifiers: Reducing the Computational Cost of Cross-Validation by Active Pattern Selection. - Friedrich Leisch; Kurt Hornik; Lakhmi C. Jain (ANNES, 1995)

ARC-LH: A New Adaptive Resampling Algorithm for Improving ANN Classifiers. - Friedrich Leisch; Kurt Hornik (NIPS, 1996)

Adaptive combination of PCA and VQ networks. - Andreas Weingessel; Horst Bischof; Kurt Hornik; Friedrich Leisch (IEEE Trans. Neural Networks, 1997)

Stationarity and Stability of Autoregressive Neural Network Processes. - Friedrich Leisch; Adrian Trapletti; Kurt Hornik (NIPS, 1998)

Cross-validation with active pattern selection for neural-network classifiers. - Friedrich Leisch; Lakhmi C. Jain; Kurt Hornik (IEEE Trans. Neural Networks, 1998)

Stationary and Integrated Autoregressive Neural Network Processes. - Adrian Trapletti; Friedrich Leisch; Kurt Hornik (Neural Comput., 2000)

Neural Techniques in Logo Recognition. - Vaijayanti Joshi; Lakhmi C. Jain; Udo Seiffert; Kathleen Zyga; Richard Price; Friedrich Leisch (HIS, 2001)

Fusion of Fuzzy System and Conventional Technique to Evaluate Weather and Terrain Effects on the Vehicle Operations. - Ajaykumar Pradhan; Lakhmi C. Jain; Arthur Filippidis; Friedrich Leisch (HIS, 2001)

Behavioral Market Segmentation of Binary Guest Survey Data with Bagged Clustering. - Sara Dolnicar; Friedrich Leisch (ICANN, 2001)

Sweave: Dynamic Generation of Statistical Reports Using Literate Data Analysis. - Friedrich Leisch (COMPSTAT, 2002)

StatDataML: An XML Format for Statistical Data. - David Meyer; Friedrich Leisch; Torsten Hothorn; Kurt Hornik (COMPSTAT, 2002)

The support vector machine under test. - David Meyer; Friedrich Leisch; Kurt Hornik (Neurocomputing, 2003)

R Version 2.0.0. - Kurt Hornik; Friedrich Leisch (Comput. Stat., 2004)

StatDataML: An XML Format for Statistical Data. - David Meyer; Friedrich Leisch; Torsten Hothorn; Kurt Hornik (Comput. Stat., 2004)

R Version 2.1.0. - Kurt Hornik; Friedrich Leisch (Comput. Stat., 2005)

Testing for Genuine Multimodality in Finite Mixture Models: Application to Linear Regression Models. - Bettina Grün; Friedrich Leisch (GfKl, 2006)

A toolbox for K. - Friedrich Leisch (Comput. Stat. Data Anal., 2006)

Fitting finite mixtures of generalized linear regressions in R. - Bettina Grün; Friedrich Leisch (Comput. Stat. Data Anal., 2007)

Compstat 2006 Young Researcher Award. - Friedrich Leisch (Comput. Stat., 2007)

Quality-Based Clustering of Functional Data: Applications to Time Course Microarray Data. - Theresa Scharl; Friedrich Leisch (GfKl, 2008)

Identifiability of Finite Mixtures of Multinomial Logit Models with Varying and Fixed Effects. - Bettina Grün; Friedrich Leisch (J. Classif., 2008)

gcExplorer: interactive exploration of gene clusters. - Theresa Scharl; Friedrich Leisch (Bioinform., 2009)

Exploratory and inferential analysis of gene cluster neighborhood graphs. - Theresa Scharl; Ingo Voglhuber; Friedrich Leisch (BMC Bioinform., 2009)

RGG: A general GUI Framework for R scripts. - Ilhami Visne; Erkan Dilaveroglu; Klemens Vierlinger; Martin Lauss; Ahmet Yildiz; Andreas Weinhäusel; Christa Noehammer; Friedrich Leisch; Albert Kriegner (BMC Bioinform., 2009)

Dealing with label switching in mixture models under genuine multimodality. - Bettina Grün; Friedrich Leisch (J. Multivar. Anal., 2009)

Mixtures of regression models for time course gene expression data: evaluation of initialization and random effects. - Theresa Scharl; Bettina Grün; Friedrich Leisch (Bioinform., 2010)

Neighborhood graphs, stripes and shadow plots for cluster visualization. - Friedrich Leisch (Stat. Comput., 2010)

Case studies in reproducibility. - Torsten Hothorn; Friedrich Leisch (Briefings Bioinform., 2011)

Weighted and robust archetypal analysis. - Manuel J. A. Eugster; Friedrich Leisch (Comput. Stat. Data Anal., 2011)

Exploratory analysis of benchmark experiments an interactive approach. - Manuel J. A. Eugster; Friedrich Leisch (Comput. Stat., 2011)

Executable Papers for the R Community: The R2 Platform for Reproducible Research. - Friedrich Leisch; Manuel J. A. Eugster; Torsten Hothorn (ICCS, 2011)

Modelling time course gene expression data with finite mixtures of linear additive models. - Bettina Grün; Theresa Scharl; Friedrich Leisch (Bioinform., 2012)

(Psycho-)analysis of benchmark experiments: A formal framework for investigating the relationship between data sets and learning algorithms. - Manuel J. A. Eugster; Friedrich Leisch; Carolin Strobl (Comput. Stat. Data Anal., 2014)

Music and timbre segmentation by recursive constrained K-means clustering. - Sebastian Krey; Uwe Ligges; Friedrich Leisch (Comput. Stat., 2014)

Benchmarking different clustering algorithms on functional data. - Christina Yassouridis; Friedrich Leisch (Adv. Data Anal. Classif., 2017)

Boosting flexible functional regression models with a high number of functional historical effects. - Sarah Brockhaus; Michael Melcher; Friedrich Leisch; Sonja Greven (Stat. Comput., 2017)

Simple K-Medoids Partitioning Algorithm for Mixed Variable Data. - Weksi Budiaji; Friedrich Leisch (Algorithms, 2019)

Effects of Resampling in Determining the Number of Clusters in a Data Set. - Rainer Dangl; Friedrich Leisch (J. Classif., 2020)

A white paper on good research practices in benchmarking: The case of cluster analysis. - Iven Van Mechelen; Anne-Laure Boulesteix; Rainer Dangl; Nema Dean; Christian Hennig; Friedrich Leisch; Douglas L. Steinley; Matthijs J. Warrens (WIREs Data. Mining. Knowl. Discov., 2023)