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  "Title": "Optimal Binning and Weight of Evidence Framework for Modeling",
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  "Authors@R": "person(given = \"José Evandeilton\",\nfamily = \"Lopes\",\nrole = c(\"aut\", \"cre\", \"cph\"),\nemail = \"evandeilton@gmail.com\",\ncomment = c(ORCID = \"0009-0007-5887-4084\"))",
  "Description": "High-performance implementation of 28 binning algorithms\n(37 implementations: 21 numerical, 16 categorical) for Weight\nof Evidence ('WoE') transformation, credit scoring, and risk\nmodeling. Methods include dynamic programming over ordered\nlevels, entropy-based ('MDLP') and chi-square ('ChiMerge')\npartitioning, isotonic regression, simulated annealing,\nkernel-density binning, sketch-based binning (KLL and\nCount-Min), and greedy merging heuristics. Features a default\nalgorithm chosen from the target type, monotonicity enforcement\nwhere the algorithm supports it, and efficient handling of\nlarge datasets via 'Rcpp'. Provides automated variable\nscreening by Information Value strength and bin ordering, and\ngeneration of the equivalent 'SQL' 'CASE' expressions for\nin-database scoring. Fully integrated with the 'tidymodels'\necosystem for building robust machine learning pipelines. Based\non methods described in Siddiqi (2006)\n<doi:10.1002/9781119201731> and Navas-Palencia (2020)\n<doi:10.48550/arXiv.2001.08025>.",
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  "Date/Publication": "2026-10-15 22:31:45 UTC",
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    ".numerical_only_algorithms",
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    "control.obwoe_scorecard",
    "ob_apply_woe_cat",
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    "ob_categorical_ivb",
    "ob_categorical_jedi",
    "ob_categorical_jedi_mwoe",
    "ob_categorical_mba",
    "ob_categorical_milp",
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    "ob_categorical_swb",
    "ob_categorical_udt",
    "ob_check_distincts",
    "ob_cutpoints_cat",
    "ob_cutpoints_num",
    "ob_numerical_bb",
    "ob_numerical_cm",
    "ob_numerical_dmiv",
    "ob_numerical_dp",
    "ob_numerical_ewb",
    "ob_numerical_fast_mdlp",
    "ob_numerical_fetb",
    "ob_numerical_ir",
    "ob_numerical_jedi",
    "ob_numerical_jedi_mwoe",
    "ob_numerical_kmb",
    "ob_numerical_ldb",
    "ob_numerical_lpdb",
    "ob_numerical_mblp",
    "ob_numerical_mdlp",
    "ob_numerical_mob",
    "ob_numerical_mrblp",
    "ob_numerical_oslp",
    "ob_numerical_sketch",
    "ob_numerical_ubsd",
    "ob_numerical_udt",
    "ob_preprocess",
    "obcorr",
    "obwoe",
    "obwoe_algorithm",
    "obwoe_algorithms",
    "obwoe_apply",
    "obwoe_bin_cutoff",
    "obwoe_gains",
    "obwoe_gains_score",
    "obwoe_gains_variable",
    "obwoe_max_bins",
    "obwoe_min_bins",
    "obwoe_prune",
    "obwoe_psi",
    "obwoe_report",
    "obwoe_scale",
    "obwoe_score",
    "obwoe_scorecard",
    "obwoe_select",
    "obwoe_sql",
    "step_obwoe"
  ],
  "_help": [
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      "title": "Categorical-Only Algorithms",
      "topics": [
        ".categorical_only_algorithms"
      ]
    },
    {
      "page": "dot-numerical_only_algorithms",
      "title": "Numerical-Only Algorithms",
      "topics": [
        ".numerical_only_algorithms"
      ]
    },
    {
      "page": "dot-universal_algorithms",
      "title": "Universal Algorithms",
      "topics": [
        ".universal_algorithms"
      ]
    },
    {
      "page": "dot-valid_algorithms",
      "title": "Valid Binning Algorithms",
      "topics": [
        ".valid_algorithms"
      ]
    },
    {
      "page": "bake.step_obwoe",
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    },
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      "title": "Control Parameters for the Scorecard Pipeline",
      "topics": [
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      ]
    },
    {
      "page": "ob_apply_woe_cat",
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      "topics": [
        "ob_apply_woe_cat"
      ]
    },
    {
      "page": "ob_apply_woe_num",
      "title": "Apply Optimal Weight of Evidence (WoE) to a Numerical Feature",
      "topics": [
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      ]
    },
    {
      "page": "ob_categorical_cm",
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      "topics": [
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      ]
    },
    {
      "page": "ob_categorical_dmiv",
      "title": "Optimal Binning for Categorical Variables using Divergence Measures",
      "topics": [
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      ]
    },
    {
      "page": "ob_categorical_dp",
      "title": "Optimal Binning for Categorical Variables using Dynamic Programming",
      "topics": [
        "ob_categorical_dp"
      ]
    },
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      "page": "ob_categorical_fetb",
      "title": "Optimal Binning for Categorical Variables using Fisher's Exact Test",
      "topics": [
        "ob_categorical_fetb"
      ]
    },
    {
      "page": "ob_categorical_gmb",
      "title": "Optimal Binning for Categorical Variables using Greedy Merge Algorithm",
      "topics": [
        "ob_categorical_gmb"
      ]
    },
    {
      "page": "ob_categorical_ivb",
      "title": "Optimal Binning for Categorical Variables using Information Value Dynamic Programming",
      "topics": [
        "ob_categorical_ivb"
      ]
    },
    {
      "page": "ob_categorical_jedi",
      "title": "Optimal Binning for Categorical Variables using JEDI Algorithm",
      "topics": [
        "ob_categorical_jedi"
      ]
    },
    {
      "page": "ob_categorical_jedi_mwoe",
      "title": "Optimal Binning for Categorical Variables with Multinomial Target using JEDI-MWoE",
      "topics": [
        "ob_categorical_jedi_mwoe"
      ]
    },
    {
      "page": "ob_categorical_mba",
      "title": "Optimal Binning for Categorical Variables using Monotonic Binning Algorithm",
      "topics": [
        "ob_categorical_mba"
      ]
    },
    {
      "page": "ob_categorical_milp",
      "title": "Optimal Binning for Categorical Variables using Heuristic Algorithm",
      "topics": [
        "ob_categorical_milp"
      ]
    },
    {
      "page": "ob_categorical_mob",
      "title": "Optimal Binning for Categorical Variables using Monotonic Optimal Binning (MOB)",
      "topics": [
        "ob_categorical_mob"
      ]
    },
    {
      "page": "ob_categorical_sab",
      "title": "Optimal Binning for Categorical Variables using Simulated Annealing",
      "topics": [
        "ob_categorical_sab"
      ]
    },
    {
      "page": "ob_categorical_sblp",
      "title": "Optimal Binning for Categorical Variables using SBLP",
      "topics": [
        "ob_categorical_sblp"
      ]
    },
    {
      "page": "ob_categorical_sketch",
      "title": "Optimal Binning for Categorical Variables using Sketch-based Algorithm",
      "topics": [
        "ob_categorical_sketch"
      ]
    },
    {
      "page": "ob_categorical_swb",
      "title": "Optimal Binning for Categorical Variables using Sliding Window Binning (SWB)",
      "topics": [
        "ob_categorical_swb"
      ]
    },
    {
      "page": "ob_categorical_udt",
      "title": "Optimal Binning for Categorical Variables using a User-Defined Technique (UDT)",
      "topics": [
        "ob_categorical_udt"
      ]
    },
    {
      "page": "ob_cutpoints_cat",
      "title": "Binning Categorical Variables using Custom Cutpoints",
      "topics": [
        "ob_cutpoints_cat"
      ]
    },
    {
      "page": "ob_cutpoints_num",
      "title": "Binning Numerical Variables using Custom Cutpoints",
      "topics": [
        "ob_cutpoints_num"
      ]
    },
    {
      "page": "ob_numerical_bb",
      "title": "Optimal Binning for Numerical Variables using Branch and Bound Algorithm",
      "topics": [
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      ]
    },
    {
      "page": "ob_numerical_cm",
      "title": "Optimal Binning for Numerical Variables using Enhanced ChiMerge Algorithm",
      "topics": [
        "ob_numerical_cm"
      ]
    },
    {
      "page": "ob_numerical_dmiv",
      "title": "Optimal Binning using Metric Divergence Measures (Zeng, 2013)",
      "topics": [
        "ob_numerical_dmiv"
      ]
    },
    {
      "page": "ob_numerical_dp",
      "title": "Optimal Binning for Numerical Variables using Dynamic Programming",
      "topics": [
        "ob_numerical_dp"
      ]
    },
    {
      "page": "ob_numerical_ewb",
      "title": "Hybrid Optimal Binning using Equal-Width Initialization and IV Optimization",
      "topics": [
        "ob_numerical_ewb"
      ]
    },
    {
      "page": "ob_numerical_fast_mdlp",
      "title": "Optimal Binning using MDLP with Monotonicity Constraints",
      "topics": [
        "ob_numerical_fast_mdlp"
      ]
    },
    {
      "page": "ob_numerical_fetb",
      "title": "Optimal Binning using Fisher's Exact Test",
      "topics": [
        "ob_numerical_fetb"
      ]
    },
    {
      "page": "ob_numerical_ir",
      "title": "Optimal Binning using Isotonic Regression (PAVA)",
      "topics": [
        "ob_numerical_ir"
      ]
    },
    {
      "page": "ob_numerical_jedi",
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