Package index • OptimalBinningWoE

All functions

AIC(<oblr>): AIC Method for oblr Objects

BIC(): Register the S3 method

BIC(<oblr>): BIC Method for oblr Objects

OBApplyWoECat(): Apply Optimal Weight of Evidence (WoE) to a Categorical Feature

OBApplyWoENum(): Apply Optimal Weight of Evidence (WoE) to a Numerical Feature

OBCalculateSpecialWoE(): Calculate Special WoE for Edge Cases

OBCreateSpecialBin(): Create Special Bin Entry

OBDataPreprocessor(): Preprocesses a numeric or categorical variable for optimal binning with handling of missing values and outliers

OBGainsTable(): Generate a Detailed Gains Table from Optimal Binning Results

OBGainsTableFeature(): Generate Gains Table for a Binned Feature

OBGetAlgoName(): Get Available Optimal Binning Algorithms

OBMapTargetVariable(): Map Target Variable to 0/1

OBPreprocessData(): Preprocess Data for Optimal Binning

OBSelectAlgorithm(): Select Optimal Binning Algorithm (Unused in main flow)

OBSelectBestModel(): Select the Best Model for Optimal Binning

OBSelectOptimalFeatures(): Select Optimal Features Based on Weight of Evidence

OBValidateInputs(): Validate Inputs for Optimal Binning

OBWoEMonotonic(): Check if WoE values are monotonic

anova(<oblr>): Anova Method for oblr Objects

binning_categorical_cutpoints(): Binning Categorical Variables using Custom Cutpoints

binning_numerical_cutpoints(): Binning Numerical Variables using Custom Cutpoints

coef(<oblr>): Coefficients Method for oblr Objects

computeMetrics(): Compute Performance Metrics for Logistic Regression Models

fit_logistic_regression(): Logistic Regression with Optional Hessian Calculation

fitted(<oblr>): Fitted Values Method for oblr Objects

logLik(<oblr>): Log-Likelihood Method for oblr Objects

oblr(): Optimized Logistic Regression

obwoe(): Optimal Binning and Weight of Evidence Calculation

optimal_binning_categorical_cm(): Optimal Binning for Categorical Variables using ChiMerge

optimal_binning_categorical_dmiv(): Optimal Binning for Categorical Variables using Divergence Measures (V2)

optimal_binning_categorical_dp(): Optimal Binning for Categorical Variables using Dynamic Programming

optimal_binning_categorical_fetb(): Categorical Optimal Binning with Fisher’s Exact Test

optimal_binning_categorical_gmb(): Categorical Optimal Binning with Greedy Merge Binning

optimal_binning_categorical_ivb(): Optimal Binning for Categorical Variables using Information Value Dynamic Programming

optimal_binning_categorical_jedi(): Optimal Categorical Binning JEDI (Joint Entropy-Driven Information Maximization)

optimal_binning_categorical_jedi_mwoe(): Optimal Binning for Categorical Variables with Multinomial Target using JEDI-MWoE

optimal_binning_categorical_mba(): Optimal Binning for Categorical Variables using Monotonic Binning Algorithm (MBA)

optimal_binning_categorical_milp(): Optimal Binning for Categorical Variables using MILP

optimal_binning_categorical_mob(): Optimal Binning for Categorical Variables using Monotonic Optimal Binning (MOB)

optimal_binning_categorical_sab(): Optimal Binning for Categorical Variables using Simulated Annealing

optimal_binning_categorical_sblp(): Optimal Binning for Categorical Variables using Similarity-Based Logistic Partitioning (SBLP)

optimal_binning_categorical_sketch(): Optimal Binning for Categorical Variables using Sketch-based Algorithm

optimal_binning_categorical_swb(): Optimal Binning for Categorical Variables using Sliding Window Binning (SWB)

optimal_binning_categorical_udt(): Optimal Binning for Categorical Variables using a User-Defined Technique (UDT)

optimal_binning_numerical_bb(): Optimal Binning for Numerical Variables using Branch and Bound Algorithm

optimal_binning_numerical_cm(): Optimal Binning for Numerical Variables using ChiMerge

optimal_binning_numerical_dmiv(): Optimal Binning for Numerical Variables using Divergence Measures and Information Value

optimal_binning_numerical_dp(): Optimal Binning for Numerical Variables using Dynamic Programming

optimal_binning_numerical_ewb(): Optimal Binning for Numerical Variables using Equal-Width Binning

optimal_binning_numerical_fast_mdlpm(): Optimal Binning for Numerical Variables using MDLP with Monotonicity

optimal_binning_numerical_fetb(): Optimal Binning for Numerical Variables with Fisher’s Exact Test

optimal_binning_numerical_ir(): Optimal Binning for Numerical Variables using Isotonic Regression

optimal_binning_numerical_jedi(): Optimal Numerical Binning JEDI (Joint Entropy-Driven Interval Discretization)

optimal_binning_numerical_jedi_mwoe(): Optimal Numerical Binning JEDI M-WOE (Multinomial Weight of Evidence)

optimal_binning_numerical_kmb(): Optimal Binning for Numerical Variables using K-means Binning (KMB)

optimal_binning_numerical_ldb(): Optimal Binning for Numerical Variables using Local Density Binning (LDB)

optimal_binning_numerical_lpdb(): Optimal Binning for Numerical Variables using Local Polynomial Density Binning (LPDB)

optimal_binning_numerical_mblp(): Optimal Binning for Numerical Features Using Monotonic Binning via Linear Programming (MBLP)

optimal_binning_numerical_mdlp(): Optimal Binning for Numerical Features using the Minimum Description Length Principle (MDLP)

optimal_binning_numerical_mob(): Optimal Binning for Numerical Features using Monotonic Optimal Binning (MOB)

optimal_binning_numerical_mrblp(): Optimal Binning for Numerical Variables using Monotonic Risk Binning with Likelihood Ratio Pre-binning (MRBLP)

optimal_binning_numerical_oslp(): Optimal Binning for Numerical Variables using OSLP

optimal_binning_numerical_sketch(): Optimal Binning for Numerical Variables using Sketch-based Algorithm

optimal_binning_numerical_ubsd(): Optimal Binning for Numerical Variables using Unsupervised Binning with Standard Deviation

optimal_binning_numerical_udt(): Optimal Binning for Numerical Variables using Unsupervised Decision Trees

predict(<oblr>): Predict Method for oblr Objects

print(<oblr>): Print Method for oblr Objects

print(<summary.oblr>): Print Method for summary.oblr Objects

residuals(<oblr>): Residuals Method for oblr Objects

summary(<oblr>): Summary Method for oblr Objects

update(<oblr>): Update Method for oblr Objects

vcov(<oblr>): Variance-Covariance Matrix Method for oblr Objects