104 citations · 166 across the 13 of their papers we have counts for
3 papers · 2 filters
Meta-Learning for Symbolic Hyperparameter Defaults
Pieter Gijsbers, Florian Pfisterer, Jan N. van Rijn +2
Hyperparameter optimization in machine learning (ML) deals with the problem of empirically learning an optimal algorithm configuration from data, usually formulated as a black-box…
deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression
David Rügamer, Chris Kolb, Cornelius Fritz +11
In this paper we describe the implementation of semi-structured deep distributional regression, a flexible framework to learn conditional distributions based on the combination of…
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…