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From Data to Decision: An Evolutionary Data-Centric AutoML Framework for Efficient and Lightweight Pipelines

https://doi.org/10.2139/ssrn.7266101
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9781118646106.ch3openalex-snapshot
Imbalanced Datasets: From Sampling to Classifiers
inferredcites →https://doi.org/10.1007/978-3-030-05318-5_6openalex-snapshot
Auto-sklearn: Efficient and Robust Automated Machine Learning
inferredcites →https://doi.org/10.1007/978-981-13-0586-3_48openalex-snapshot
Instance Selection Using Multi-objective CHC Evolutionary Algorithm
inferredcites →https://doi.org/10.1007/s13222-022-00413-2openalex-snapshot
Data Cleaning and AutoML: Would an Optimizer Choose to Clean?
inferredcites →https://doi.org/10.1016/j.eswa.2010.09.087openalex-snapshot
Determining the optimal re-sampling strategy for a classification model with imbalanced data using design of experiments and response surface methodologies
inferredcites →https://doi.org/10.1016/j.knosys.2012.11.005openalex-snapshot
Genetic algorithms in feature and instance selection
inferredcites →https://doi.org/10.1109/tpami.2021.3051276openalex-snapshot
AutoML for Multi-Label Classification: Overview and Empirical Evaluation
inferredcites →https://doi.org/10.1145/2908812.2908918openalex-snapshot
Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science
inferredcites →https://doi.org/10.1145/3411764.3445306openalex-snapshot
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows
inferredcites →https://doi.org/10.1186/s12864-019-6413-7openalex-snapshot
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
inferredcites →https://doi.org/10.1371/journal.pone.0041882openalex-snapshot
A Comparison of MCC and CEN Error Measures in Multi-Class Prediction
inferredcites →https://doi.org/10.1613/jair.1.11854openalex-snapshot
Benchmark and Survey of Automated Machine Learning Frameworks
inferredcites →https://doi.org/10.3390/app132011583openalex-snapshot
Improving Automated Machine-Learning Systems through Green AI
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