ml-explainability

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AmirhosseinHonardoust / Exit-Narrative-Generator

An explanation-first HR analytics system that reconstructs why employee exit becomes rational. Instead of predicting attrition, it generates human-readable exit narratives by decomposing pressure and retention forces, adding peer context and counterfactual interventions to reveal how stability erodes over time.

counterfactual-analysis logistic-regression decision-support people-analytics interpretable-ml explainable-ai systems-thinking human-centered-ai retention-analysis hr-analytics data-storytelling streamlit-app attrition-analysis ml-explainability non-stationary-systems instability-modeling narrative-modeling organizational-dynamics peer-comparison failure-as-process

Updated Dec 18, 2025
Python

AmirhosseinHonardoust / Car-Value-Decomposition-Theory

Star 17

This article explores the theory behind explainable car pricing using value decomposition, showing how machine learning models can break a predicted price into intuitive components such as brand premium, age depreciation, mileage influence, condition effects, and transmission or fuel-type adjustments.

random-forest predictive-modeling sensitivity-analysis machine-learning-theory interpretable-ml explainable-ai model-interpretability economic-modeling feature-attribution applied-ml consumer-analytics value-decomposition data-science-methods transparent-ai pricing-intelligence automotive-analytics car-price-modeling ml-explainability automotive-ml explainable-pricing

Updated Dec 10, 2025
Python

Shravani018 / xai-credit-risk-analysis

Star 0

A credit risk prediction project that compares multiple machine learning models and applies explainable AI methods to interpret and analyze model decisions.

risk-analysis random-forest lime credit-risk shap ml-explainability