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This article discusses some basic properties of learning using web-based simulation with the focus on different types of learning goals (instructional goals) and on proper instructional strategies (pedagogical strategies) for web-based simulation.
"One of the properties of learning with logic is that the learning can happen very, very quickly, in the sense of only needing one or two examples".
The statistical learning theory, in essence, characterizes properties of learning machines to make them able of generalization to unseen data.
In this section we outline some formal properties of learning objects so that they might be incorporated in future adaptive systems.
Machine leaning is a field of research that formally focuses on the theory, performance, and properties of learning systems and algorithms.
An alternative explanation, in terms of a triangle model, would be that there is no special representational status of morphemes, and that they are emergent properties of learning relations among phonology, orthography and meaning [34].
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This is because NN have the property of learning from cases and thus they can tackle difficult problems which cannot be solved with mathematical algorithm based on rules.
Empirical prediction models include, among others, the neural network (NN) models that are known to have the property of learning from cases and with ability to handle complex nonlinear physical phenomena.
In line with the previous literature about the temporal properties of motor learning [ 1, 35] a quick improvement was observed in the early stages of the practice, while the learning curve became flatter in later learning stages.
This indicates that CSI FingerId and other machine-learning approaches are capable of learning inherent properties from the mass spectra, beyond simple spectral similarity.
This property is fundamental to the construction of learning curves [ 4– 10].
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