Document classification and machine learning technology in eDiscovery are gaining attention under new names such as technology-assisted review (TAR), machine-assisted review (MAR), computer-assisted review (CAR) and predictive coding. 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
A recent US ruling by Judge Peck regarding the use of machine learning technology in legal review, has created a lot of tumult in the eDiscovery community (see http://www.law.com/jsp/lawtechnologynews/PubArticleLTN.jsp?
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