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  "Title": "Case Based Reasoning",
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  "Date": "2026-02-26",
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  "Description": "Case-based reasoning is a problem-solving methodology that\ninvolves solving a new problem by referring to the solution of\na similar problem in a large set of previously solved problems.\nThe key aspect of Case Based Reasoning is to determine the\nproblem that \"most closely\" matches the new problem at hand.\nThis is achieved by defining a family of distance functions and\nusing these distance functions as parameters for local\naveraging regression estimates of the final result. The optimal\ndistance function is chosen based on a specific error measure\nused in regression estimation. This approach allows for\nefficient problem-solving by leveraging past experiences and\nadapting solutions from similar cases. The underlying concept\nis inspired by the work of Dippon J. et al. (2002)\n<doi:10.1016/S0167-9473(02)00058-0>.",
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    "message": "Prepare v0.4.1 for CRAN submission\n\nBump version to 0.4.1, add NEWS changelog, move Rcpp/RcppParallel\nfrom Depends to Imports, remove unused stats::ar import, replace\nrequire(ranger) with library(ranger) in examples, update license\nyear, add .Rbuildignore exclusions, and create cran-comments.md.\n\nCo-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>\n",
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      "date": "2018-06-12"
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      "date": "2026-02-27"
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    "CoxModel",
    "depth_distance",
    "distance_random_forest",
    "distanceRandomForest",
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    "generate_grid",
    "LinearModel",
    "LogisticModel",
    "proximity_distance",
    "ranger_forests_to_matrix",
    "RFModel",
    "terminal_nodes",
    "terminalNodes",
    "weighted_distance",
    "weightedDistance"
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      "title": "Converts a distance vector into an object of class 'dist'",
      "topics": [
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        "as_dist_object"
      ]
    },
    {
      "page": "CBRBase",
      "title": "Root class for common functionality of this package",
      "topics": [
        "CBRBase"
      ]
    },
    {
      "page": "CoxModel",
      "title": "Cox-Beta Model for Case-Based-Reasoning",
      "topics": [
        "CoxModel"
      ]
    },
    {
      "page": "depth_distance",
      "title": "Depth Distance",
      "topics": [
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      ]
    },
    {
      "page": "distance_random_forest",
      "title": "Distance calculation based on RandomForest Proximity or Depth",
      "topics": [
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        "distance_random_forest"
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    },
    {
      "page": "edges_between_terminal_nodes",
      "title": "Number of Edges between Terminal Nodes",
      "topics": [
        "edges_between_terminal_nodes"
      ]
    },
    {
      "page": "generate_grid",
      "title": "Generate Grid",
      "topics": [
        "generate_grid"
      ]
    },
    {
      "page": "LinearModel",
      "title": "Linear Regression Model for Case-Based-Reasoning",
      "topics": [
        "LinearModel"
      ]
    },
    {
      "page": "LogisticModel",
      "title": "Logistic Regression Model for Case-Based-Reasoning",
      "topics": [
        "LogisticModel"
      ]
    },
    {
      "page": "predict.CoxModel",
      "title": "Predict method for CoxModel",
      "topics": [
        "predict.CoxModel"
      ]
    },
    {
      "page": "predict.LinearModel",
      "title": "Predict method for LinearModel",
      "topics": [
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      ]
    },
    {
      "page": "predict.LogisticModel",
      "title": "Predict method for LogisticModel",
      "topics": [
        "predict.LogisticModel"
      ]
    },
    {
      "page": "predict.RFModel",
      "title": "Predict method for RFModel",
      "topics": [
        "predict.RFModel"
      ]
    },
    {
      "page": "print.CoxModel",
      "title": "Print method for CoxModel",
      "topics": [
        "print.CoxModel"
      ]
    },
    {
      "page": "print.LinearModel",
      "title": "Print method for LinearModel",
      "topics": [
        "print.LinearModel"
      ]
    },
    {
      "page": "print.LogisticModel",
      "title": "Print method for LogisticModel",
      "topics": [
        "print.LogisticModel"
      ]
    },
    {
      "page": "print.RFModel",
      "title": "Print method for RFModel",
      "topics": [
        "print.RFModel"
      ]
    },
    {
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      "title": "Get proximity matrix of an ranger object",
      "topics": [
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      ]
    },
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      "title": "Forest2Matrix",
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    },
    {
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      "title": "Root class for Regression Models, e.g., CPH, logistic, and linear regression",
      "topics": [
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      "title": "RandomForest Model for Searching Similar Cases",
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        "terminal_nodes"
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