Making Learners (More) Monotone

Viering, Tom J.; Mey, Alexander; Loog, Marco

doi:10.1007/978-3-030-44584-3_42

Cited by 9 publications

(7 citation statements)

References 17 publications

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“…Except for trehalulose, all other α‐D‐glucosyl‐D‐fructoses reported a testing accuracy of 1.0000. The learning curve is derived during the evaluation of a model when an increasing amount of events randomly selected from the whole training set was fed into the program for training [44] . According to the learning curve results, a minimum of 648 training data events, equivalent to about 100 events per analyte, is sufficient to achieve a 0.98 overall accuracy of the model (Figure 4c).…”

Section: Resultsmentioning

confidence: 99%

Discrimination of Disaccharide Isomers of Different Glycosidic Linkages Using a Modified MspA Nanopore

Zhang,

Cao,

Fan

et al. 2024

Angew Chem Int Ed

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Disaccharides are composed of two monosaccharide subunits joined by a glycosidic linkage in an α or β configuration. Different combinations of isomeric monosaccharide subunits and different glycosidic linkages result in different isomeric disaccharide products. Thus, direct discrimination of these disaccharide isomers from a mixture is extremely difficult. In this paper, a hetero‐octameric Mycobacterium smegmatis porin A (MspA) nanopore conjugated with a phenylboronic acid (PBA) adapter was applied for disaccharide sensing, with which three most widely known disaccharides in nature, including sucrose, lactose and maltose, were clearly discriminated. Besides, all six isomeric α‐D‐glucopyranosyl‐D‐fructoses, differing only in their glycosidic linkages, were also well resolved. Assisted by a custom machine learning algorithm, a 0.99 discrimination accuracy is achieved. Nanopore discrimination of disaccharide isomers with different glycosidic linkages, which has never been previously demonstrated, is inspiring for nanopore saccharide sequencing. This sensing capacity was also applied in direct identification of isomaltulose additives in a commercial sucrose‐free yogurt, from which isomaltulose, lactose and L‐lactic acid were simultaneously detected.

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Section: Resultsmentioning

confidence: 99%

Discrimination of Disaccharide Isomers of Different Glycosidic Linkages Using a Modified MspA Nanopore

Zhang,

Cao,

Fan

et al. 2024

Angew Chem Int Ed

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“…The teacher's method selection aims to make it easier for students to understand the lesson as determined by the situation and condition. Furthermore, to support the statement Viering et al (2020) said that a method could be monotonous and tedious if the teacher was unable to create an exciting learning process.…”

Section: Discussionmentioning

confidence: 99%

Charade Game: Does it Impact Students’ Writing Ability?

Azhar

Prastikawati²,

Musarokah³

2023

ETERNAL

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Modern English instruction must show a developing strategy to motivate and inspire pupils. Introducing games into the teaching and learning process is an option for reducing student boredom. The game of Charade is one alternate teaching strategy that can be used to teach English writing and improve students' writing skills. This study utilized the Charade game as a teaching method for writing. Utilizing a pre-test and post-test, a quasi-experimental research method was implemented. 30 students were assigned to each of the control and experimental groups, for a total of 60. After a series of interventions, students' writing skills were assessed. The outcome of quantitative data analysis was performed using SPSS 25. Compared to the control group, the experimental group demonstrates a considerable change and improvement in writing skills. The significant improvement of the experimental group demonstrates the efficacy of the Charade game as a method for teaching writing.

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“…This allows them to determine when to switch to a model trained with more data. In contrast to [198], they argue that their second algorithm does not learn slower, as its generalization bound coincides with a known lower bound of regular supervised learning.…”

Section: Monotonicity: a General Fix?mentioning

confidence: 90%

“…One may wonder, however, whether generally applicable approaches exist that can turn any learner into a monotone one. A first attempt is made in [198] which proposes a wrapper that, with high probability, makes any classifier monotone in terms of the the error rate. The main idea is to consider n as a variable over which model selection is performed.…”

Section: Monotonicity: a General Fix?mentioning

confidence: 99%

The Shape of Learning Curves: a Review

Viering¹,

Loog²

2021

Preprint

Self Cite

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Learning curves provide insight into the dependence of a learner's generalization performance on the training set size. This important tool can be used for model selection, to predict the effect of more training data, and to reduce the computational complexity of model training and hyperparameter tuning. This review recounts the origins of the term, provides a formal definition of the learning curve, and briefly covers basics such as its estimation. Our main contribution is a comprehensive overview of the literature regarding the shape of learning curves. We discuss empirical and theoretical evidence that supports well-behaved curves that often have the shape of a power law or an exponential. We consider the learning curves of Gaussian processes, the complex shapes they can display, and the factors influencing them. We draw specific attention to examples of learning curves that are ill-behaved, showing worse learning performance with more training data. To wrap up, we point out various open problems that warrant deeper empirical and theoretical investigation. All in all, our review underscores that learning curves are surprisingly diverse and no universal model can be identified.

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Making Learners (More) Monotone

Cited by 9 publications

References 17 publications

Discrimination of Disaccharide Isomers of Different Glycosidic Linkages Using a Modified MspA Nanopore

Discrimination of Disaccharide Isomers of Different Glycosidic Linkages Using a Modified MspA Nanopore

Charade Game: Does it Impact Students’ Writing Ability?

The Shape of Learning Curves: a Review

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