{ "_id": "6a1ee586b401979e7341136e", "Package": "DALEX", "Title": "moDel Agnostic Language for Exploration and eXplanation", "Version": "2.5.3", "Authors@R": "c(person(\"Przemyslaw\", \"Biecek\", email = \"przemyslaw.biecek@gmail.com\", role = c(\"aut\", \"cre\"), \ncomment = c(ORCID = \"0000-0001-8423-1823\")),\nperson(\"Szymon\", \"Maksymiuk\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-3120-1601\")),\nperson(\"Hubert\", \"Baniecki\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-6661-5364\")))", "Description": "Any unverified black box model is the path to failure.\nOpaqueness leads to distrust. Distrust leads to ignoration.\nIgnoration leads to rejection. DALEX package xrays any model\nand helps to explore and explain its behaviour. Machine\nLearning (ML) models are widely used and have various\napplications in classification or regression. Models created\nwith boosting, bagging, stacking or similar techniques are\noften used due to their high performance. But such black-box\nmodels usually lack direct interpretability. DALEX package\ncontains various methods that help to understand the link\nbetween input variables and model output. Implemented methods\nhelp to explore the model on the level of a single instance as\nwell as a level of the whole dataset. All model explainers are\nmodel agnostic and can be compared across different models.\nDALEX package is the cornerstone for 'DrWhy.AI' universe of\npackages for visual model exploration. 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