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Feature interaction provides insight into hidden domain knowledge and interactive structure of a data set.
After the appearance of a new dialectal feature, interaction between speakers who have adopted this feature and those who have not leads to the expansion or the curtailment of its area or even to its disappearance.
In this paper, we discuss the feature interaction problem before introducing our tool for Feature Interaction Detection (FID).
Feature interaction is considered during the selection step used to create new populations.
The feature interaction detection framework is applied to identify discriminating connectivity patterns of selected informative voxels.
Substantial evidence is presented that illustrates the inadequate documentation, bad implementation, feature interaction, and feature incoherence.
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This result is used to motivate feature selection guidelines that take into account feature interactions.
One of the significant examples is property that is formed by feature interactions.
When feature interactions occur, it may become even worse to identify the regular patterns of the primary features.
The reason for these deviations are feature interactions (Siegmund et al. 2013), i.e., the selection of one feature influences non-functional properties of other features.
In CIDE, feature interactions become apparent when colors denote different feature overlap (in this cases the colors are blended in the overlapping region).
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