Titlebook: Second-order Learning in Developmental Evaluation; New Methods for Comp Andrew Mitchell Book 2019 The Editor(s) (if applicable) and The Aut

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The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Andrew MitchellProvides a Developmental Education framework which augments traditional monitoring and evaluation.Details a case study investigating the sustainability of a town in the UK.Investigates how project lea

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https://doi.org/10.1007/978-3-319-99371-3project learning; developmental evaluation; enactive cognition; cognitive science; second-order learning

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Andrew Mitchellinator offers the user several models to build predictive systems with. This paper explores which ML models (in Wekinator) are the most useful for predicting an output in the context of interactive music composition. We use two performance gestures for piano, with opposing datasets, to train availab

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Andrew Mitchellinator offers the user several models to build predictive systems with. This paper explores which ML models (in Wekinator) are the most useful for predicting an output in the context of interactive music composition. We use two performance gestures for piano, with opposing datasets, to train availab

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Andrew Mitchellperformers from a randomly chosen parameter set. Our experiments are conducted on datasets from the recently expanded UCR time series archive. We demonstrate the usability improvements to randomised BOSS with a case study using a large whale acoustics dataset for which BOSS proved infeasible.