33 citations · 157 across the 27 of their papers we have counts for
Showing 2021 · stat.MLShow all
2 papers · 2 filters
stat.ML2021★ 8 cited
Interpretable transformed ANOVA approximation on the example of the prevention of forest fires
Daniel Potts, Michael Schmischke
The distribution of data points is a key component in machine learning. In most cases, one uses min-max normalization to obtain nodes in or Z-score normalization for standa…
stat.ML2021★ 15 cited
Interpretable Approximation of High-Dimensional Data
Daniel Potts, Michael Schmischke
In this paper we apply the previously introduced approximation method based on the ANOVA (analysis of variance) decomposition and Grouped Transformations to synthetic and real data…