{ "_id": "6a15441eacfb0bcc41d56b57", "Package": "randomForestExplainer", "Title": "Explaining and Visualizing Random Forests in Terms of Variable\nImportance", "Version": "0.11.0", "Authors@R": "c(\nperson(\"Aleksandra\", \"Paluszynska\", email = \"ola.paluszynska@gmail.com\", role = c(\"aut\")),\nperson(\"Przemyslaw\", \"Biecek\", email = \"przemyslaw.biecek@gmail.com\", role = c(\"aut\",\"ths\")),\nperson(\"Michael\", \"Mayer\", email = \"mayermichael79@gmail.com\", role = c(\"aut\")),\nperson(\"Olivier\", \"Roy\", role = c(\"aut\")),\nperson(\"Yue\", \"Jiang\", email = \"rivehill@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-9798-5517\"))\n)", "Description": "A set of tools to help explain which variables are most\nimportant in a random forests. Various variable importance\nmeasures are calculated and visualized in different settings in\norder to get an idea on how their importance changes depending\non our criteria (Hemant Ishwaran and Udaya B. Kogalur and Eiran\nZ. Gorodeski and Andy J. Minn and Michael S. 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