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This text file contains the dataset to be classified, and the relationship between a set of attributes is shown.
The decision matrix of an MADM problem with n alternatives and p attributes is shown in Table 1.
The capability of auditory models to discriminate the three considered music attributes is shown via the normal-hearing auditory model which is compared to the state-of-the-art methods.
We present three attributes from within this dataset: A1=Ba,A2=Ca and A3=Fe and due to limited space and the size of the dataset only a subset of values for these three attributes is shown.
The distribution of these results for different attributes is shown in Figure S1.
The complex relationship between formulation design factors, manufacturing unit operations, and their corresponding quality attributes is shown in Fig. 1.
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These attributes are shown in Table 7.
These attributes are shown in Fig. 3.
The basic management attributes are shown in Table 1.
These four attributes are shown in Fig. 5 without WFCs.
Seven of these attributes are shown in Figs. 7, 8, 9 and 10.
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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