168 citations · 656 across the 19 of their papers we have counts for
3 papers · 1 filter
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges
Bernd Bischl, Martin Binder, Michel Lang +9
Most machine learning algorithms are configured by one or several hyperparameters that must be carefully chosen and often considerably impact performance. To avoid a time consuming…
Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features
Florian Pargent, Florian Pfisterer, Janek Thomas +1
Since most machine learning (ML) algorithms are designed for numerical inputs, efficiently encoding categorical variables is a crucial aspect in data analysis. A common problem are…
Deep Semi-Supervised Learning for Time Series Classification
Jann Goschenhofer, Rasmus Hvingelby, David Rügamer +3
While Semi-supervised learning has gained much attention in computer vision on image data, yet limited research exists on its applicability in the time series domain. In this work,…