Sentence examples for within datasets from inspiring English sources

We demonstrate the conceptual benefit of ensemble learning, emphasizing on the requirement of diversity within datasets, given to sub-ensembles, rather than the common misconception of data availability requirement for improved prediction.

CSEM used generative adversarial networks (GANs) — which consist of deep neural net architectures composed of two networks, pitting one against the other — to define clusters within datasets.

Contextual anomaly detection seeks to find relationships within datasets where variations in external behavioural attributes well describe anomalous results in the data.

As neither ranges nor benchmarks for relational indicators have been established, we discuss our findings in a relative sense, comparing metrics within datasets across three metropolitan areas.

In certain situations, such as in the Caribbean Sea example below, single element "normative calculations" (e.g., Leinen 1987) are sufficient, while in other cases multiple different analytical and/or computational approaches need to be simultaneously deployed to develop a more holistic understanding of the geochemical variability within datasets.

This could be considered as the information layer and would answer questions such as "At what granularity should data be made available or citable?", "What is an ELN record?" and "If single datasets are given identifiers, what about collections of datasets, files within datasets or individual data?".

The overall process of the within-dataset experiment is illustrated in Fig. 2A.

The process for selecting the feature set was similar to the one used in the within-dataset experiments.

Pyrosequencing de-noising algorithms such as Pyronoise [29] aim to reduce this by within-dataset analysis, but are computationally costly.

Additionally, combining datasets was shown to increase performance on a test dataset, especially when using integrated-within dataset normalisation, with best data fit obtained by Loess_XPN.

In this context, three different approaches, (one standard and two integrative), were used for within-dataset normalisation and compared for each dataset previously described.