R: Optimal Binning and Weight of Evidence Framework for Modeling

# Optimal Binning and Weight of Evidence Framework for Modeling

## Documentation for package ‘OptimalBinningWoE’ version 1.0.8

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

.categorical_only_algorithms | Categorical-Only Algorithms
.numerical_only_algorithms | Numerical-Only Algorithms
.universal_algorithms | Universal Algorithms
.valid_algorithms | Valid Binning Algorithms
bake.step_obwoe | Apply the Optimal Binning Transformation
control.obwoe | Control Parameters for Optimal Binning Algorithms
fit_logistic_regression | Fit Logistic Regression Model
obcorr | Compute Multiple Robust Correlations Between Numeric Variables
obwoe | Unified Optimal Binning and Weight of Evidence Transformation
obwoe_algorithm | Binning Algorithm Parameter
obwoe_algorithms | List Available Algorithms
obwoe_apply | Apply Weight of Evidence Transformations to New Data
obwoe_bin_cutoff | Bin Cutoff Parameter
obwoe_gains | Gains Table Statistics for Credit Risk Scorecard Evaluation
obwoe_max_bins | Maximum Bins Parameter
obwoe_min_bins | Minimum Bins Parameter
ob_apply_woe_cat | Apply Optimal Weight of Evidence (WoE) to a Categorical Feature
ob_apply_woe_num | Apply Optimal Weight of Evidence (WoE) to a Numerical Feature
ob_categorical_cm | Optimal Binning for Categorical Variables using Enhanced ChiMerge Algorithm
ob_categorical_dmiv | Optimal Binning for Categorical Variables using Divergence Measures
ob_categorical_dp | Optimal Binning for Categorical Variables using Dynamic Programming
ob_categorical_fetb | Optimal Binning for Categorical Variables using Fisher's Exact Test
ob_categorical_gmb | Optimal Binning for Categorical Variables using Greedy Merge Algorithm
ob_categorical_ivb | Optimal Binning for Categorical Variables using Information Value Dynamic Programming
ob_categorical_jedi | Optimal Binning for Categorical Variables using JEDI Algorithm
ob_categorical_jedi_mwoe | Optimal Binning for Categorical Variables with Multinomial Target using JEDI-MWoE
ob_categorical_mba | Optimal Binning for Categorical Variables using Monotonic Binning Algorithm
ob_categorical_milp | Optimal Binning for Categorical Variables using Heuristic Algorithm
ob_categorical_mob | Optimal Binning for Categorical Variables using Monotonic Optimal Binning (MOB)
ob_categorical_sab | Optimal Binning for Categorical Variables using Simulated Annealing
ob_categorical_sblp | Optimal Binning for Categorical Variables using SBLP
ob_categorical_sketch | Optimal Binning for Categorical Variables using Sketch-based Algorithm
ob_categorical_swb | Optimal Binning for Categorical Variables using Sliding Window Binning (SWB)
ob_categorical_udt | Optimal Binning for Categorical Variables using a User-Defined Technique (UDT)
ob_cutpoints_cat | Binning Categorical Variables using Custom Cutpoints
ob_cutpoints_num | Binning Numerical Variables using Custom Cutpoints
ob_gains_table | Compute Comprehensive Gains Table from Binning Results
ob_gains_table_feature | Compute Gains Table for a Binned Feature Vector
ob_numerical_bb | Optimal Binning for Numerical Variables using Branch and Bound Algorithm
ob_numerical_cm | Optimal Binning for Numerical Variables using Enhanced ChiMerge Algorithm
ob_numerical_dmiv | Optimal Binning using Metric Divergence Measures (Zeng, 2013)
ob_numerical_dp | Optimal Binning for Numerical Variables using Dynamic Programming
ob_numerical_ewb | Hybrid Optimal Binning using Equal-Width Initialization and IV Optimization
ob_numerical_fast_mdlp | Optimal Binning using MDLP with Monotonicity Constraints
ob_numerical_fetb | Optimal Binning using Fisher's Exact Test
ob_numerical_ir | Optimal Binning using Isotonic Regression (PAVA)
ob_numerical_jedi | Optimal Binning using Joint Entropy-Driven Interval Discretization (JEDI)
ob_numerical_jedi_mwoe | Optimal Binning for Multiclass Targets using JEDI M-WOE
ob_numerical_kmb | Optimal Binning using K-means Inspired Initialization (KMB)
ob_numerical_ldb | Optimal Binning for Numerical Variables using Local Density Binning
ob_numerical_lpdb | Optimal Binning using Local Polynomial Density Binning (LPDB)
ob_numerical_mblp | Optimal Binning for Numerical Features Using Monotonic Binning via Linear Programming
ob_numerical_mdlp | Optimal Binning for Numerical Features using Minimum Description Length Principle
ob_numerical_mob | Optimal Binning for Numerical Features using Monotonic Optimal Binning
ob_numerical_mrblp | Optimal Binning for Numerical Features using Monotonic Risk Binning with Likelihood Ratio Pre-binning
ob_numerical_oslp | Optimal Binning for Numerical Variables using Optimal Supervised Learning Partitioning
ob_numerical_sketch | Optimal Binning for Numerical Variables using Sketch-based Algorithm
ob_numerical_ubsd | Optimal Binning for Numerical Variables using Unsupervised Binning with Standard Deviation
ob_numerical_udt | Optimal Binning for Numerical Variables using Entropy-Based Partitioning
ob_preprocess | Data Preprocessor for Optimal Binning
plot.obwoe | Plot Method for obwoe Objects
plot.obwoe_gains | Plot Gains Table
prep.step_obwoe | Prepare the Optimal Binning Step
print.obwoe | Print Method for obwoe Objects
print.step_obwoe | Print Method for step_obwoe
required_pkgs.step_obwoe | Required Packages for step_obwoe
step_obwoe | Optimal Binning and WoE Transformation Step
summary.obwoe | Summary Method for obwoe Objects
tidy.step_obwoe | Tidy Method for step_obwoe
tunable.step_obwoe | Tunable Parameters for step_obwoe