The phrase "any pair of features" is correct and usable in written English.
It can be used when referring to two specific characteristics or attributes among a larger set of features in various contexts, such as technology, design, or analysis.
Example: "In this study, we will analyze the impact of any pair of features on user satisfaction."
Alternatives: "any two features" or "any combination of features".
Therefore, the covariance in a given region depends on the sum of each feature dimension z(i i = 1⋯n, as well as the sum of the multiplications of any pair of features z (i) z (j i,j = 1⋯ n, requiring in total n F + n F 2 / 2 integral images, one for each feature dimension z (i) and one for the multiplication of any pair of feature dimensions z (i z(j) (the covariance matrix is symmetric).
The uncorrelated condition means that for any pair of features, the two sets of features are independent, given the label.
For any pair of features with a Spearman correlation coefficient larger than 0.96, one feature was randomly selected to be kept, and the other was removed from the selection.
Decomposing each feature sample as a weighted linear combination of the other feature samples, TPLRMC can measure the similarities between any pairs of feature samples.
Truffaut lent his name to the project as screenwriter (in effect, agreeing to sign his name to Godard's script), and Claude Chabrol, who had made a pair of features, pretended to serve as "technical adviser".
For this study, the Euclidean distance measure is used to formulate the match score between a pair of features.
We obtain a matching decision function to classify a pair of features as a true or false match.
Games of pretense in particular, and imaginative episodes in general, tend to share a pair of features that have been dubbed mirroring and quarantining.
But a pair of features worth caring about are user-bound come early 2012, according to Google developer advocate Paul Kinlan, who spoke recently at the Develop conference in Liverpool.
Liaison can be viewed as a set, usually a pair, of features in proximity with which process information can be associated.
If the correlation of a pair of features is 0.6 or higher, we consider one feature in the pair to be redundant, and remove the feature with a lower mutual information value.
