interpretability


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in·ter·pret

 (ĭn-tûr′prĭt)
v. in·ter·pret·ed, in·ter·pret·ing, in·ter·prets
v.tr.
1. To explain the meaning of: The newspapers interpreted the ambassador's speech as an attempt at making peace. See Synonyms at explain.
2. To understand the significance of; construe: interpreted his smile to be an agreement; interpreted the open door as an invitation.
3. To present or conceptualize the meaning of by means of art or criticism: The actor interpreted the character with great subtlety.
4. To translate from one language into another: interpreted the ambassador's remarks for the assembly.
v.intr.
To serve as an interpreter for speakers of different languages.
[Middle English interpreten, from Old French interpreter, from Latin interpretārī, from interpres, interpret-, negotiator, explainer; see per- in Indo-European roots.]
in·ter′pret·a·bil′i·ty, in·ter′pret·a·ble·ness n.
in·ter′pret·a·ble adj.

interpretability

Suitability of imagery for interpretation with respect to answering adequately requirements on a given type of target in terms of quality and scale. a. poor--Imagery is unsuitable for interpretation to answer adequately requirements on a given type of target. b. fair--Imagery is suitable for interpretation to answer requirements on a given type of target but with only average detail. c. good--Imagery is suitable for interpretation to answer requirements on a given type of target in considerable detail. d. excellent--Imagery is suitable for interpretation to answer requirements on a given type of target in complete detail.
References in periodicals archive ?
Responses were used to improve the interpretability of the questionnaire and to help design the classification system (see Table 2) for the qualitative data produced from the closed-answer question.
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When interpretability is important - for example, in many medical applications - you need a trained human in the decision-making loop.
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The other filtering techniques like Wiener filter [12] is used to improve the interpretability or sensitivity of information to provide the better input.
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After this transformation, Size was mean-centered to improve parameter interpretability.
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It is a good idea to examine several possible models and choose among them on the basis of interpretability, parsimony, and ease of variable acquisition.
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