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This repository has been archived by the owner on Feb 8, 2024. It is now read-only.
Be able to locate samples in the domain based on a condition. Conditions might be, for instance,
presence of missing data points
high/low concentration of observations
Given a condition, we should obtain a subset of points, maybe clustered in subregions, on which we can perform different actions, for instance, randomly select a subsample.
Possible sub-problems
Filter points based on condition (locate all not-nan points)
Cluster filtered points in sub-regions (use proximity of the elements they belong to?)
Randomly sample points on a filtered group
Introduce a notion of proximity, i.e., given a point, locate the nearest point
Sample points at random on the neighborood of a clustered region
Allow to identify regions with highest/lowest points concentration
The text was updated successfully, but these errors were encountered:
Overview
Be able to locate samples in the domain based on a condition. Conditions might be, for instance,
Given a condition, we should obtain a subset of points, maybe clustered in subregions, on which we can perform different actions, for instance, randomly select a subsample.
Possible sub-problems
The text was updated successfully, but these errors were encountered: