We introduce a simple strategy for AutoML that does not require a pipeline optimisation process (making it more scalable and less prone to overfitting) and does not rely on extracted meta-features. The proposed approach, named AutoEn, is a simple yet effective ensemble-based AutoML method for the automatic generation and optimisation of ensembles from a predefined set of pipelines composed of a sequence of preprocessing techniques plus one ML classifier. The novelty of our method lies in automatically generating sets of competitive pipelines without focusing on the fine-tuning of these pipelines. Thus, we conceive a new and much simpler approach that achieves a competitive performance in comparison to the results reported in the state-of-the-art.
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