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Output: (k) appropriate attribute clusters with their representative attributes.
Step 9 The final clusters and their centers as the representative attributes are then output.
Step 9 Output the final clusters and their centers as the representative attributes.
The main purpose of attribute clustering was to select representative attributes to replace the whole set.
After Step 9, (k) clusters of attributes are formed and (k) representative attributes for the feature space are found.
After that, the proposed MNF attribute clustering algorithm is used to partition the feature space into (k) clusters and output the (k) representative attributes of the clusters.
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Each cluster can thus be represented by its representative attribute.
It is defined as the average distance between an attribute and its representative attribute in the same cluster.
Denote (A_{c} = {A_{1}^{c}, A_{2}^{c}, {ldots }, A_{k}^{c}}subseteq A) as the initial representative attribute set.
This feature is important to the proposed attribute clustering here, since not only the attributes are clustered but also the representative attribute of each cluster has to be found.
A Cadbury representative attributed the margin improvement to ongoing cost savings as part of the "Vision Into Action" restructuring plan, but admitted that falling advertising rates had also helped.
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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