Abstract: The present disclosure relates to systems, methods and computer readable media for evaluating performance of a machine learning system and providing one or more performance views representative of the determined performance. For example, systems disclosed herein may receive or identify performance information including outputs, accuracy data, and feature data associated with a plurality of test instances. In addition, systems disclosed herein may provide one or more performance views via a graphical user interface including graphical elements (e.g., interactive elements) and indications of accuracy data and other performance data with respect to feature clusters associated with select groupings of test instances from the plurality of test instances. The performance views may include interactive features to enable a user to view and intuitively understand performance of the machine learning system with respect to clustered groupings of test instances that share common characteristics.

Abstract: Methods, computer readable mediums and systems provide media player users with a full contextual metadata experience. Metadata include multiple forms of property data, or information, relating to media accessed by a media player, such as a CD in a CD-ROM drive of a computer. Metadata is transferred from a server to a client. Identification parameters associated with the accessed media file are submitted by the client to a server, and property data is retrieved and forwarded to the client. The metadata provides the user with integrated, contemporaneous property data directly related to the media file being played, providing automatic, integrated access to data from multiple databases, simply by accessing a related media file through a media player, without further direction from the user.