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Box plot representations, frequency distribution plots, and scatter plots of the dataset are provided to enrich its value.
We present a deep recurrent autoencoder model that learns richly structured multi-view plot representations from raw book text, approximating such preferences.
We propose a principled and scalable framework leveraging expert-provided semantic tags (e.g., mystery, pirates) to evaluate plot representations in an extrinsic fashion, assessing their ability to produce locally coherent groupings of novels (micro-clusters) in model space.
A web interface for easy handling of job and model submission and management has been built adopting the python framework Flask [32], and using Open Babel [27] and matplotlib [33] modules for structure and plot representations.
Such analyses were performed through the use of box plot representations, improving the methodology used by Cárdenas et al. [21].
a Dot plot representations of populations defined by FSC, SSC, CD1c, CD21, CD5, CD19 and CD23.
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a, Arch plot representation of short and long-range RNA-RNA interactions along the ZIKV genome.
(g) Contour plot representation of the PES in (f).
Fig. 5 Radar plot representation of the behavior of structural and functional parameters.
A box plot representation of these parameters is shown in Fig. 3.
(d) The classical line plot representation of the same data with (c).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com