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In that context, feature selection is becoming an essential requirement in many data mining applications.
An example of context feature bias is when a word can have different meanings in two domains.
In addition, the Nikkei will also start feeding articles into Evernote's Context feature, which launched last month.
Context feature bias occurs when there are conditional distribution differences between the domains as a feature in one domain may have a different meaning in another.
This approach is most appropriate when the source and target have the same class label space and one can transform Xs and Xt without context feature bias.
To resolve context feature bias, a method to augment the source and target feature space with three duplicate copies of the original feature set is proposed.
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The new findings, team members say, may undercut old theories or put them in a more subtle context featuring a mix of behavioral and physiological aids that let marine mammals plumb the depths.
Table 3 compares the performance with and without the shape context features.
Table 2 shows the best classification result for the skating dataset with shape context features.
Table 4 shows the best performance achieved with shape context features.
In today's Smartphone eco-systems, such context features can be obtained easily.
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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