Marcellinus Aditya WitarsahCredit Scorecard Modelling with optbinningWeight of Evidence and Logistic RegressionJun 161
Luís Fernando TorresLogistic Regression in Credit Risk: The Role of Weight of Evidence and Information ValueOptimizing Performance and Simplicity in White Box ModelsAug 27, 20231
InTowards AIbyVarun NakraHow To Use Target Encoding in Machine Learning Credit Risk Models — Part 2In my previous story Part 1 of this topic —…Jun 5Jun 5
Anik ChakrabortyWeight of Evidence (WoE) and Information Value (IV) — how to use it in EDA and Model Building?Weight of Evidence (WoE) and Information Value (IV) can be used to understand the predictive power of an independent variable. WoE helps to…Sep 5, 20214Sep 5, 20214
InTowards AIbyVarun NakraHow To Use Target Encoding in Machine Learning Credit Risk Models — Part 1Target encoding, also known as mean encoding or likelihood encoding, is a technique used to convert categorical variables into numerical…Jun 3Jun 3
Marcellinus Aditya WitarsahCredit Scorecard Modelling with optbinningWeight of Evidence and Logistic RegressionJun 161
Luís Fernando TorresLogistic Regression in Credit Risk: The Role of Weight of Evidence and Information ValueOptimizing Performance and Simplicity in White Box ModelsAug 27, 20231
InTowards AIbyVarun NakraHow To Use Target Encoding in Machine Learning Credit Risk Models — Part 2In my previous story Part 1 of this topic —…Jun 5
Anik ChakrabortyWeight of Evidence (WoE) and Information Value (IV) — how to use it in EDA and Model Building?Weight of Evidence (WoE) and Information Value (IV) can be used to understand the predictive power of an independent variable. WoE helps to…Sep 5, 20214
InTowards AIbyVarun NakraHow To Use Target Encoding in Machine Learning Credit Risk Models — Part 1Target encoding, also known as mean encoding or likelihood encoding, is a technique used to convert categorical variables into numerical…Jun 3
Anna PershukovaToo many categories: how to deal with categorical features of high cardinalityHave you ever tried to one-hot encode categorical variable with lots of different values when your dataset is of humble size?Nov 10, 2020
Natasha MashanovichWeight of Evidence Transformation: A Universal Modeling GemPushing boundaries: Transforming Weight of Evidence in propensity modeling beyond credit risks.Mar 25
Wen ZhangCreate reason code via SHAP value for GMB modelBrief: Explored generating reason codes for a binary Gradient Boosting Model using Python’s SHAP package. Used breast cancer dataset…Mar 20, 2023
