The phrase "a given attribute" is correct and usable in written English.
It can be used when referring to a specific characteristic or quality that has been specified or identified in a particular context.
Example: "In this analysis, we will focus on a given attribute that significantly influences user behavior."
Alternatives: "a specified characteristic" or "a particular feature".
Within a given attribute, the relative differences between the levels correspond to the relative respondent preferences.
Conversely, if all thresholds used were not met, no cuts were created for a given attribute.
We combine color-coding and sorting on a given attribute to reinforce the perception of grouped leaves of similar values.
Nevertheless, the reference sequence problem remains: probabilities must always be relativized to a collective, and for a given attribute such as 'heads' there are infinitely many.
The information gain is a good measure to determine how well a given attribute separates the training instances according to their target class.
However, attribute selection approaches to date typically treat all values within a given attribute equally, and thus focus on the general importance of all values within a given attribute, or combinations of the full set of different attributes' values [17, 18].
To avoid random fluctuations in determining the importance of any given attribute, a reference set of 'shadow attributes' is used for deciding which attributes are truly important, since the importance of a shadow attribute can be non-zero only due to random fluctuations [ 22].
Each given attribute, A j, has a continuous set of values, which can be sorted and then denoted as val1…val b.
The frequency ratio (FR) is the ratio of the probability of an occurrence to the probability of a non-occurrence for given attributes (Bonham-Carter 1994).
This would imply that therapeutic strategies have to be custom-tailored for each mechanism and used in a combinatorial manner to give attribute to all disease manifestations.
Entropy is a measure of randomness or dispersion of a given discrete attribute.
