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Found 5 papers, 1 papers with code
Selecting Optimal Trace Clustering Pipelines with AutoML
Trace clustering has been extensively used to preprocess event logs.
Using Meta-learning to Recommend Process Discovery Methods
Process discovery methods have obtained remarkable achievements in Process Mining, delivering comprehensible process models to enhance management capabilities.
Improved prediction of soil properties with Multi-target Stacked Generalisation on EDXRF spectra
In this study, we proposed the Multi-target Stacked Generalisation (MTSG), a novel MTR method relying on learning from different regressors arranged in stacking structure for a boosted outcome.
Towards meta-learning for multi-target regression problems
In this paper, we propose a meta-learning system to recommend the best predictive method for a given multi-target regression problem.
Online Local Boosting: improving performance in online decision trees
To increase predictive performance without largely increasing memory and time costs, this paper introduces a novel algorithm, named Online Local Boosting (OLBoost), which can be combined into online decision tree algorithms to improve their predictive performance without modifying the structure of the induced decision trees.
