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These include ratings of emotional response and problem improvement with respect to problems related to psychosis and qualitative feedback related to therapy gains and disappointments.
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Sizes of discovered clusters, with respect to Problem Context2.
Profile representatives of two clusters (with 'high' and 'low' academic capability), with respect to Problem Context2.
Comparison of graduate and dropout cases, with respect to Problem Context1.
Sizes of discovered clusters, with respect to Problem Context1 Fig. 12 Cluster Context2.
We further show that the proposed algorithm and implementations scale linearly with respect to problem and machine sizes.
DB measures with different number of clusters (k), with respect to Problem Context1 Fig. 8 Dunn Context1.
If and are feasible with respect to Problem (18) at tree node s, then the bound dnext is tight.
Dunn measures with different number of clusters (k), with respect to Problem Context2 Fig. 11 Cluster Context1.
Dunn measures with different number of clusters (k), with respect to Problem Context1 Fig. 9 DB Context2.
Profile representatives of two clusters (with 'high' and 'low' school-level academic capability), with respect to Problem Context1.
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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