127 skills found · Page 4 of 5
AmirhosseinHonardoust / Exit Narrative GeneratorAn 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.
AmirhosseinHonardoust / Disaster Instability Early Warning EngineAn early-warning system that models disasters as instability transitions rather than isolated events. It combines force-based instability modeling with an interpretable ML escalation-risk layer to detect when hazards become disasters due to exposure growth, response delays, and buffer collapse.
AmirhosseinHonardoust / Car Value Decomposition TheoryThis 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.
AmirhosseinHonardoust / Irreversible Degradation Threshold DetectorAn interpretable battery health engine that detects hidden points of no return instead of just predicting health %. It models stress, buffer, and degradation intensity, discovers Stable/Drifting/Irreversible regimes via GMM, and learns simple Decision Tree thresholds, with a Streamlit app for diagnostics and what-if scenarios.
slds-lmu / ImlplotsCreate Interpretable Machine Learning plots with an interactive Shiny based dashboard
AmirhosseinHonardoust / Physiological Debt Accumulation EngineA systems-level analysis engine that models sleep as a recovery debt process rather than a nightly outcome. Using physiological traits and ecological pressure signals, it estimates predicted sleep need, quantifies sleep debt, and visualizes how stress accumulates silently before visible fatigue or failure occurs.
adc-trust-ai / Trust FreeAn interpretable regression model in Python with Random-Forest-level accuracy
AmirhosseinHonardoust / Skill Adaptation Debt EngineA Streamlit dashboard that measures skill adaptation debt instead of predicting outcomes. It decomposes pressure into churn, novelty, and breadth to explain which roles/industries are becoming harder to staff. Includes role/industry reports, skill pressure maps, what-if scenario simulation, and a dataset explorer.
dcfeng-87 / Interpretable ML Shear Squat WallDeveloping an interpretable machine learning model for predicting the shear strength of RC squat walls using XGBoost and SHAP.
AlexIoannides / Lime Interpretable MlAn example of how the LIME algorithm can be used to provide real-world insight into the decision processes of a 'black-box' machine learning algorithm - in this case a Radom Forest regressor.
pnxenopoulos / Cav KerasConcept activation vectors for Keras
h2oai / Article Information 2019Article for Special Edition of Information: Machine Learning with Python
ngpepin / Stylometric TransferInterpretable stylometric profiling + author-style transfer built on explicit and LLM-genenated JSON fingerprints and local measurements. Fingerprint your corpus, inspect/visualize signals, then LLM-generate stylistically similar text with meaning preserved, deterministic post-processing, normalization controls, and deviation reports. CLI + API.
MaartenGr / InterpretableMLMy analyses for interpretable Machine Learning
JYLFamily / Interpert Machine Learninghttps://christophm.github.io/interpretable-ml-book/index.html
InflixOP / Anomaly Detection Using Explainable AIThis project integrates Explainable AI (XAI) techniques for anomaly detection in encrypted network traffic using ML Algorithms. We employ SHAP (SHapley Additive Explanations) to interpret model decisions and enhance transparency in detecting malicious activities. The system is designed to identify suspicious patterns in encrypted traffic.
manujosephv / Interpretability BlogThe notebooks used to demonstrate the blog post about Interpretability in ML
wuhanstudio / Interpretable Ml Covid 19Interpretable Machine Learning for COVID-19
allianceai / EndgameA unified framework for tabular, time-series, and multimodal machine learning
data-avengers-girls / GHC19 Interpreting ML ModelsCoding exercises for workshop on Breaking the Black Box: Interpreting ML Models
