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  "Package": "DALEXtra",
  "Title": "Extension for 'DALEX' Package",
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  "Description": "Provides wrapper of various machine learning models. In\napplied machine learning, there is a strong belief that we need\nto strike a balance between interpretability and accuracy.\nHowever, in field of the interpretable machine learning, there\nare more and more new ideas for explaining black-box models,\nthat are implemented in 'R'. 'DALEXtra' creates 'DALEX' Biecek\n(2018) <doi:10.48550/arXiv.1806.08915> explainer for many type\nof models including those created using 'python' 'scikit-learn'\nand 'keras' libraries, and 'java' 'h2o' library. Important part\nof the package is Champion-Challenger analysis and innovative\napproach to model performance across subsets of test data\npresented in Funnel Plot.",
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  "URL": "https://ModelOriented.github.io/DALEXtra/,\nhttps://github.com/ModelOriented/DALEXtra",
  "BugReports": "https://github.com/ModelOriented/DALEXtra/issues",
  "Repository": "https://modeloriented.r-universe.dev",
  "Date/Publication": "2026-01-14 01:10:18 UTC",
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      "date": "2019-09-19"
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    },
    {
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      "date": "2019-11-18"
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      "date": "2020-03-29"
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    "explain_mlr3",
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    "funnel_measure",
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    "overall_comparison",
    "predict_model.dalex_explainer",
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    "predict_surrogate_iml",
    "predict_surrogate_lime",
    "predict_surrogate_local_model",
    "training_test_comparison"
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      "title": "Compare machine learning models",
      "topics": [
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      ]
    },
    {
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      "title": "Create your conda virtual env with DALEX",
      "topics": [
        "create_env"
      ]
    },
    {
      "page": "dalex_load_explainer",
      "title": "DALEX load explainer",
      "topics": [
        "dalex_load_explainer"
      ]
    },
    {
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      "title": "Create explainer from your h2o model",
      "topics": [
        "explain_h2o"
      ]
    },
    {
      "page": "explain_keras",
      "title": "Wrapper for Python Keras Models",
      "topics": [
        "explain_keras"
      ]
    },
    {
      "page": "explain_mlr",
      "title": "Create explainer from your mlr model",
      "topics": [
        "explain_mlr"
      ]
    },
    {
      "page": "explain_mlr3",
      "title": "Create explainer from your mlr model",
      "topics": [
        "explain_mlr3"
      ]
    },
    {
      "page": "explain_scikitlearn",
      "title": "Wrapper for Python Scikit-Learn Models",
      "topics": [
        "explain_scikitlearn"
      ]
    },
    {
      "page": "explain_tidymodels",
      "title": "Create explainer from your tidymodels workflow.",
      "topics": [
        "explain_tidymodels"
      ]
    },
    {
      "page": "explain_xgboost",
      "title": "Create explainer from your xgboost model",
      "topics": [
        "explain_xgboost"
      ]
    },
    {
      "page": "funnel_measure",
      "title": "Caluculate difference in performance in models across different categories",
      "topics": [
        "funnel_measure"
      ]
    },
    {
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      "title": "Exract info from model",
      "topics": [
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        "model_info.H2OBinomialModel",
        "model_info.H2OMultinomialModel",
        "model_info.H2ORegressionModel",
        "model_info.keras",
        "model_info.LearnerClassif",
        "model_info.LearnerRegr",
        "model_info.model_stack",
        "model_info.scikitlearn_model",
        "model_info.workflow",
        "model_info.WrappedModel",
        "model_info.xgb.Booster"
      ]
    },
    {
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      "title": "Compare champion with challengers globally",
      "topics": [
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      ]
    },
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      "title": "Funnel plot for difference in measures",
      "topics": [
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      ]
    },
    {
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      "title": "Plot function for overall_comparison",
      "topics": [
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    },
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      "title": "Plot and compare performance of model between training and test set",
      "topics": [
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    },
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      "title": "Instance Level Surrogate Models",
      "topics": [
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        "plot.predict_surrogate_lime",
        "predict_model.dalex_explainer",
        "predict_parts",
        "predict_parts_break_down",
        "predict_parts_ibreak_down",
        "predict_parts_shap",
        "predict_surrogate",
        "predict_surrogate_iml",
        "predict_surrogate_lime",
        "predict_surrogate_local_model"
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      "topics": [
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      "topics": [
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