16 citations · 30 across the 4 of their papers we have counts for
9 papers
Subgroup detection in linear growth curve models with generalized linear mixed model (GLMM) trees
Marjolein Fokkema, Achim Zeileis
Growth curve models are popular tools for studying the development of a response variable within subjects over time. Heterogeneity between subjects is common in such models, and re…
Imputation of missing values in multi-view data
Wouter van Loon, Marjolein Fokkema, Frank de Vos +3
Data for which a set of objects is described by multiple distinct feature sets (called views) is known as multi-view data. When missing values occur in multi-view data, all feature…
Improved prediction rule ensembling through model-based data generation
Benny Markovitch, Marjolein Fokkema
Prediction rule ensembles (PRE) provide interpretable prediction models with relatively high accuracy.PRE obtain a large set of decision rules from a (boosted) decision tree ensemb…
Analyzing hierarchical multi-view MRI data with StaPLR: An application to Alzheimer's disease classification
Wouter van Loon, Frank de Vos, Marjolein Fokkema +4
Multi-view data refers to a setting where features are divided into feature sets, for example because they correspond to different sources. Stacked penalized logistic regression (S…
View selection in multi-view stacking: Choosing the meta-learner
Wouter van Loon, Marjolein Fokkema, Botond Szabo +1
Multi-view stacking is a framework for combining information from different views (i.e. different feature sets) describing the same set of objects. In this framework, a base-learne…
The Early Roots of Statistical Learning in the Psychometric Literature: A review and two new results
Mark de Rooij, Bunga Citra Pratiwi, Marjolein Fokkema +2
Machine and Statistical learning techniques become more and more important for the analysis of psychological data. Four core concepts of machine learning are the bias variance trad…