K. Hornik

Publications409
h-index70
Citations61,461
Highly Influential Citations3,111
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Bioconductor: open software development for computational biology and bioinformatics
TLDR
Details of the aims and methods of Bioconductor, the collaborative creation of extensible software for computational biology and bioinformatics, and current challenges are described.
Multilayer feedforward networks are universal approximators
Unbiased Recursive Partitioning: A Conditional Inference Framework
TLDR
A unified framework for recursive partitioning is proposed which embeds tree-structured regression models into a well defined theory of conditional inference procedures and it is shown that the predicted accuracy of trees with early stopping is equivalent to the prediction accuracy of pruned trees with unbiased variable selection.
Approximation capabilities of multilayer feedforward networks
  • K. Hornik
  • Computer Science
    Neural Networks
  • 1 March 1991
Neural networks and principal component analysis: Learning from examples without local minima
Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks
kernlab - An S4 Package for Kernel Methods in R
TLDR
The package contains dot product primitives (kernels), implementations of support vector machines and the relevance vector machine, Gaussian processes, a ranking algorithm, kernel PCA, kernel CCA, and a spectral clustering algorithm.
Implementing a Class of Permutation Tests: The coin Package
TLDR
A computational framework is established in coin that likewise embeds the corresponding R functionality in a common S4 class structure with associated generic functions, inherit the flexibility of the underlying theory and conditional inference functions for important special cases can be set up easily.
topicmodels: An R Package for Fitting Topic Models
TLDR
The R package topicmodels provides basic infrastructure for fitting topic models based on data structures from the text mining package tm to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent variables.
Model-Based Recursive Partitioning
TLDR
An algorithm for model-based recursive partitioning is suggested that yields a partitioned (or segmented) parametric model that can be effectively visualized and that subject-matter scientists are used to analyzing and interpreting.
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