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You are viewing ARCHIVED CONTENT released online between 1 April 2010 and 24 August 2018 or content that has been selectively archived and is no longer active. Content in this archive is NOT UPDATED, and links may not function.Extract from article by Bill Dimm published by ACEDS
You may already be familiar with the precision-recall curve, which describes the performance of a predictive coding system. Unfortunately, the precision-recall curve doesn’t (normally) display any information about the cost of training the system, so it isn’t convenient when you want to compare the effectiveness of different training methodologies. This article looks at the gain curve, which is better suited for that purpose.
The gain curve shows how the recall achieved depends on the number of documents reviewed (slight caveat to that at the end of the article). Recall is the percentage of all relevant documents that have been found. High recall is important for defensibility.
Read the complete article at Gain Curves