The following pages link to partykit (Q22593):
Displaying 21 items.
- Interval forecasts based on regression trees for streaming data (Q2036138) (← links)
- Network trees: a method for recursively partitioning covariance structures (Q2065251) (← links)
- An explicit split point procedure in model-based trees allowing for a quick fitting of GLM trees and GLM forests (Q2066746) (← links)
- A note on the structural change test in highly parameterized psychometric models (Q2088928) (← links)
- Computation and application of generalized linear mixed model derivatives using \textit{lme4} (Q2088938) (← links)
- Subgroup identification in individual participant data meta-analysis using model-based recursive partitioning (Q2103863) (← links)
- Ensemble learning from model based trees with application to differential price sensitivity assessment (Q2127069) (← links)
- Ordinal trees and random forests: score-free recursive partitioning and improved ensembles (Q2169870) (← links)
- Count regression trees (Q2183647) (← links)
- Applied Predictive Modeling (Q2874155) (← links)
- Modern data science with R (Q2959035) (← links)
- Measuring the Stability of Results From Supervised Statistical Learning (Q3391150) (← links)
- Random forests, decision trees, and categorical predictors: the ``absent levels'' problem (Q4558194) (← links)
- Appraisal of Performance of Three Tree-Based Classification Methods (Q4689247) (← links)
- Tree aggregation for random forest class probability estimation (Q4970316) (← links)
- A Tree-Based Semi-Varying Coefficient Model for the COM-Poisson Distribution (Q5066752) (← links)
- Tree-Based Methods for Statistical Learning in R (Q5086662) (← links)
- (Q5856838) (← links)
- (Q5886023) (← links)
- LTRCforests (Q5979442) (← links)
- coat (Q5983558) (← links)
