"selected instances" is a correct and usable phrase in written English.
You could use it to describe particular examples of something, such as "The study reviewed a range of selected instances of workplace bullying."
He has selected instances of factual errors, grammatical mistakes and inappropriate court reporting.
"We see selected instances," she said, "but that does not mean that it is being done to a great extent throughout the industry.
The Office Assistant was designed to give instant aid to users, either by popping up at selected instances or by allowing the user to type in questions about the Word program in its search box.
[30] compute diversity within selected instances from their conditional error.
[24] suggest a batch mode active learning relying on the Fisher information matrix to ensure small redundancy among selected instances.
Computational results on the selected instances show that the algorithm on average outperforms the myopic policy by 23 28%, depending on the parametric design.
The mean pairwise disconnectivity index of its instances is 0.0039: that is only about 0.4% of all connected pairs of genes become suspended when a randomly selected instance of this motif is deleted from the network.
Weights (W) or quality estimates for each attribute (A) are estimated based on whether the nearest neighbor (nearest hit, H) of a randomly selected instance (R) from the same class and the nearest neighbor from the other class (nearest miss, M) have the same or different values.
Investigating the subject with finely-honed critical instincts, they have applied stringent tests in selecting instances they consider to be credible, and have rejected many cases they held to be fraudulent or inadequately attested.
D-Confidence is an active learning approach that tends to explore unseen regions in instance space, thus selecting instances from unseen classes faster with fewer queries than traditional active learning approaches.
The active learning methods used are: Distance (DIST), a simple margin method which samples training instances based on their proximity to a support vector machine (SVM) hyperplane; Diversity (DIV) which selects instances based on their diversity/dissimilarity from instances in the training set.
