1. A computer-implemented method for transparent data loss prevention classifications, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying a document that received a classification by a machine learning classifier for data loss prevention; identifying at least one linguistic constituent within the document that contributed to the classification; identifying a relevant passage of the document that contextualizes the linguistic constituent; displaying a user interface comprising the linguistic constituent in context of the relevant passage; receiving user input via the user interface indicating a type of mistake, selected via the user interface from a plurality of types of mistakes, that potentially caused the machine learning classifier to misclassify the document, wherein indicating the type of mistake that potentially caused the machine learning classifier to misclassify the document comprises indicating a basis of classification relied upon by the machine learning classifier that resulted in the machine learning classifier misclassifying the document.
1. A computer-implemented method for transparent data loss prevention classifications, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying a document that received a classification by a machine learning classifier for data loss prevention; identifying at least one linguistic constituent within the document that contributed to the classification; identifying a relevant passage of the document that contextualizes the linguistic constituent; displaying a user interface comprising the linguistic constituent in context of the relevant passage; receiving user input via the user interface indicating a type of mistake, selected via the user interface from a plurality of types of mistakes, that potentially caused the machine learning classifier to misclassify the document, wherein indicating the type of mistake that potentially caused the machine learning classifier to misclassify the document comprises indicating a basis of classification relied upon by the machine learning classifier that resulted in the machine learning classifier misclassifying the document. 4. The computer-implemented method of claim 1 , further comprising modifying the machine learning classifier in response to receiving the user input indicating the type of mistake.