PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics
-
Updated
Mar 30, 2025 - Jupyter Notebook
#
model-diagnostics
Here are 45 public repositories matching this topic...
Implementation of NAACL 2024 Outstanding Paper "LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models"
-
Updated
Mar 13, 2025 - Python
🔍 AI-powered diagnosis for Scikit-learn models: Detect overfitting, data leakage, class imbalance & more with LLM-generated insights
python data-science machine-learning ai deep-learning scikit-learn sklearn overfitting mlops model-diagnostics llm langchain
-
Updated
Jan 30, 2026 - Python
This repository commits to the application of biostatistics knowledge on clinical, randomized trials and observational studies.
variable-selection survival-analysis logistic-regression mixed-effects-models model-diagnostics missing-value-imputation propensity-score-matching
-
Updated
Oct 1, 2024 - HTML
Tool for evaluating atmospheric carbon dioxide concentrations as simulated by Earth system models
-
Updated
Sep 2, 2022 - Jupyter Notebook
Sub-package of spatstat containing functionality for parametric modelling and inference
influence statistical-inference confidence-intervals spatial-analysis parameter-estimation poisson-process leverage gibbs-process cluster-process analysis-of-variance determinantal-point-processes model-diagnostics spatial-modelling neyman-scott spatial-point-processes cox-process
-
Updated
Jun 19, 2026 - R
Auto-diagnose deep learning training pathologies: overfitting, unstable LR, exploding gradients, noisy training, and early stopping issues.
machine-learning python-library ml overfitting ml-library model-diagnostics model-optimization training-diagnostics
-
Updated
May 12, 2026 - HTML
Polyhedron is a domain-driven Python optimization modeling framework that turns business entities into transparent MILP/MIQP models, with built-in diagnostics, scenario analysis, and robust solver interoperability.
python optimization milp pyomo operations-research scip mip mixed-integer-programming scenario-analysis modeling-framework model-diagnostics decision-optimization miqp
-
Updated
May 13, 2026 - Python
This project uses the Reaction Time Survey dataset to develop a linear regression model for accurately predicting student reaction times based on various predictors. Tech: R (RStudio)
r exploratory-data-analysis lasso hypothesis-testing multiple-linear-regression vif model-diagnostics
-
Updated
Jul 16, 2024
This repository contains some of the time series analysis, diagnostics and forecasting projects I have done.
timeseries forecasting rprogramming time-series-analysis model-diagnostics tsa-package forecast-package
-
Updated
Jan 15, 2023 - Jupyter Notebook
Approximation Bayesian Computation: Population Monte Carlo in MATLAB and Python
approximate-bayesian-computation population-monte-carlo transition-density likelihood-free-inference posterior-sampling model-diagnostics summary-metrics epsilon-adaptation
-
Updated
Mar 4, 2025 - Python
Tool for evaluating atmospheric carbon dioxide concentrations as simulated by Earth system models
-
Updated
Aug 29, 2022 - Jupyter Notebook
Explain why your model fails — not just how accurate it is.
visualization python data-science machine-learning scikit-learn model-evaluation error-analysis explainable-ai xai streamlit model-diagnostics
-
Updated
Feb 3, 2026 - Python
Low-cost plasticity diagnostics for reinforcement learning models.
debugging reinforcement-learning deep-learning pytorch rl plasticity model-diagnostics analysis-tool
-
Updated
Apr 11, 2026 - Python
A two-parameter Weibull lens on transformer weights — diagnose weight-magnitude distributions (shape k, scale λ) across 7 model families, and explain how λ evolves under AdamW training. Library (npm-weibull-py) + benchmark database + companion code for arXiv:2605.18898 and 2606.19367.
machine-learning deep-learning transformers neural-networks arxiv interpretability weibull-distribution adamw-optimizer training-dynamics model-diagnostics large-language-models llm weight-analysis
-
Updated
Jun 19, 2026 - Python
Global challenge to create Species Distribution Model to predict occurrence of frog species, Litoria fallax, in Australia.
-
Updated
Jun 9, 2022 - Jupyter Notebook
Nine diagnostic tools for detecting and understanding overfitting in scikit-learn models — polynomial overfitting, learning curves, validation curves, bias-variance decomposition, regularisation sweeps, data leakage detection, and more. Companion code for the ML Diagnostics Mastery series.
machine-learning scikit-learn regularization overfitting learning-curves data-leakage bias-variance-tradeoff model-diagnostics validation-curves ml-best-practices
-
Updated
Apr 6, 2026 - Python
time series analysis in R use cases
time-series r-markdown forecasting data-analysis autocorrelation r-programming non-stationary heteroscedasticity model-diagnostics
-
Updated
Jul 8, 2023
Objective of this project is to perform predictive assesment on the Gross Domestic Product of India through an inferential analysis of various socio-economic factors to find out which predictors contribute most to the GDP. Various models are compared and Stepwise Regression model is implemented which resulted in 5.7% Test MSE.
-
Updated
Jan 5, 2020
🩺 Diagnose model issues in scikit-learn with evidence-based insights and LLM-powered analysis for improved machine learning performance.
python data-science machine-learning ai deep-learning scikit-learn overfitting mlops model-diagnostics llm langchain
-
Updated
Jun 16, 2026 - Python
Improve this page
Add a description, image, and links to the model-diagnostics topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the model-diagnostics topic, visit your repo's landing page and select "manage topics."