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The Impact of Incorrect Training Sets and Rolling Collections on Technology-Assisted Review (TAR) and Defensible Disposition

Several judicial rulings, white papers and conferences have addressed typical legal concerns in relation to the quality of machine learning. In the paper we address two of these very common concerns in document reduction and legal review and investigate their relation with machine learning quality in more detail. First, we investigated the impact of the quality of training documents on the overall classification results and the use of machine learning with Support Vector Machines

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