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Meta-learning is an attempt to understand data a priori of executing a learning algorithm.
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According to Kelly et al. [17], concept drift occurs due to alterations on the following probabilities of data production: A priori of classes P ω1),…,P(ω M ), i.e. alteration on the relative size of a given class or the appearance of new classes.
The toolbox allows the integration of quantitative measurement data, a priori knowledge of parameters and states, and qualitative information on the dynamic or steady-state behavior.
The experimental results demonstrate the improvement of the proposed methods in terms of the source estimation accuracy and also show that exploiting the two a priori of the data, namely the nonnegativity of the mixing matrix and the statistical independence of the sources, allows us to achieve better estimation results.
Finally, a strength of the investigation was the development a priori of standardized data abstraction tools and criteria for each disease group, with samples analyzed only for cases identified as definite or highly probable.
Of these polymorphic CpGs, appropriate interpretation of methylation data requires a priori knowledge of each individual's genotype.
As the ULS estimation procedure does not require multivariate normal distribution of the data, no a priori normalisation of the observed variables was applied [ 33].
Based on existing data and a priori knowledge of the exposure and outcome of interest in all the studies, we decided that maternal age and gestational age were the main "important" potential confounders for all the included studies.
In contrast, no alleles were observed in Dokai Bay that were not also observed in Tokyo Bay. STRUCTURE analysis of nuclear microsatellite data without a priori classification of populations indicates that Japanese Carcinus are substantially diverged from their native congeners (Figure 4).
For the observatory hourly means further problems were discovered by fitting hour-by-hour spherical harmonic models to the data with a priori estimates of known signals removed.
This use of computational strategies will potentially lead to discoveries from omics data without a priori knowledge of the system.
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