jphall663/awesome-machine-learning-interpretability

A curated list of awesome responsible machine learning resources.

Size: 1.44 MB - Last synced: about 21 hours ago - Pushed: 1 day ago - Stars: 3,463 - Forks: 575

SelfExplainML/PiML-Toolbox

PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics

Language: Jupyter Notebook - Size: 242 MB - Last synced: 1 day ago - Pushed: 2 days ago - Stars: 874 - Forks: 106

interpretml/DiCE

Generate Diverse Counterfactual Explanations for any machine learning model.

Language: Python - Size: 15.2 MB - Last synced: 1 day ago - Pushed: 28 days ago - Stars: 1,280 - Forks: 179

salesforce/OmniXAI

OmniXAI: A Library for eXplainable AI

Language: Jupyter Notebook - Size: 64.2 MB - Last synced: about 8 hours ago - Pushed: 21 days ago - Stars: 814 - Forks: 85

edahelsinki/pyslise

Robust regression algorithm that can be used for explaining black box models (Python implementation)

Language: Python - Size: 3.55 MB - Last synced: 3 days ago - Pushed: 4 days ago - Stars: 5 - Forks: 1

ModelOriented/treeshap

Compute SHAP values for your tree-based models using the TreeSHAP algorithm

Language: R - Size: 17.7 MB - Last synced: 3 days ago - Pushed: 4 months ago - Stars: 75 - Forks: 21

ModelOriented/vivo

Variable importance via oscillations

Language: R - Size: 5.14 MB - Last synced: 4 days ago - Pushed: over 3 years ago - Stars: 14 - Forks: 3

ModelOriented/DALEX

moDel Agnostic Language for Exploration and eXplanation

Language: Python - Size: 798 MB - Last synced: 3 days ago - Pushed: 10 days ago - Stars: 1,330 - Forks: 166

IBM/AutoPeptideML

AutoML system for building trustworthy peptide bioactivity predictors

Language: Python - Size: 3.4 MB - Last synced: 4 days ago - Pushed: 5 days ago - Stars: 10 - Forks: 0

explainX/explainx

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]

Language: Jupyter Notebook - Size: 61.2 MB - Last synced: about 23 hours ago - Pushed: 2 months ago - Stars: 393 - Forks: 54

marcovirgolin/gpg

Re-implementation of GP-GOMEA that attempts to be simpler to understand and use than the original.

Language: C++ - Size: 431 KB - Last synced: 6 days ago - Pushed: 7 days ago - Stars: 8 - Forks: 1

davideferrari92/multiobjective_symbolic_regression

This is a Python library that implements a Multi-objective Symbolic Regression algorithm. It can be used as a Machine Learning algorithm to create predictive models in the form of mathematical expressions.

Language: Python - Size: 1.31 MB - Last synced: 7 days ago - Pushed: 8 days ago - Stars: 10 - Forks: 2

zju-vipa/awesome-neural-trees

Introduction, selected papers and possible corresponding codes in our review paper "A Survey of Neural Trees"

Size: 1.66 MB - Last synced: about 4 hours ago - Pushed: over 1 year ago - Stars: 72 - Forks: 6

rachtibat/zennit-crp

An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization

Language: Jupyter Notebook - Size: 17.9 MB - Last synced: 5 days ago - Pushed: about 1 month ago - Stars: 97 - Forks: 11

sergioburdisso/pyss3

A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI :octocat:)

Language: Python - Size: 102 MB - Last synced: 3 days ago - Pushed: 9 months ago - Stars: 332 - Forks: 44

PlantedML/randomPlantedForest

Random Planted Forest

Language: C++ - Size: 96.7 MB - Last synced: 14 days ago - Pushed: 21 days ago - Stars: 3 - Forks: 2

lopusz/awesome-interpretable-machine-learning

Language: Python - Size: 1.47 MB - Last synced: 4 days ago - Pushed: about 1 year ago - Stars: 900 - Forks: 140

yasithdev/robustml

Out of Distribution Detection via Hypothesis Testing

Language: Jupyter Notebook - Size: 733 MB - Last synced: 12 days ago - Pushed: 13 days ago - Stars: 2 - Forks: 1

carpentries-incubator/high-dimensional-analysis-in-python

Language: Jupyter Notebook - Size: 50.2 MB - Last synced: 11 days ago - Pushed: 12 days ago - Stars: 0 - Forks: 4

fzi-forschungszentrum-informatik/TSInterpret

An Open-Source Library for the interpretability of time series classifiers

Language: Python - Size: 129 MB - Last synced: 12 days ago - Pushed: about 1 month ago - Stars: 101 - Forks: 8

PlantedML/Planted_Forest

Interpretable machine learning algorithm

Language: R - Size: 1.48 MB - Last synced: 14 days ago - Pushed: about 1 year ago - Stars: 3 - Forks: 2

ModelOriented/survex

Explainable Machine Learning in Survival Analysis

Language: R - Size: 309 MB - Last synced: 13 days ago - Pushed: 29 days ago - Stars: 88 - Forks: 10

pbiecek/xai_resources

Interesting resources related to XAI (Explainable Artificial Intelligence)

Language: R - Size: 13.2 MB - Last synced: 14 days ago - Pushed: almost 2 years ago - Stars: 783 - Forks: 133

dswah/pyGAM

[HELP REQUESTED] Generalized Additive Models in Python

Language: Python - Size: 15.5 MB - Last synced: 10 days ago - Pushed: about 1 month ago - Stars: 839 - Forks: 152

anselmeamekoe/TabSRA

Use an intrinsically interpretable model or explain a black box?

Language: Jupyter Notebook - Size: 28.1 MB - Last synced: 15 days ago - Pushed: 16 days ago - Stars: 3 - Forks: 1

ModelOriented/kernelshap

Efficient R implementation of SHAP

Language: R - Size: 2.36 MB - Last synced: 17 days ago - Pushed: 4 months ago - Stars: 30 - Forks: 7

dandls/counterfactuals

counterfactuals: An R package for Counterfactual Explanation Methods

Language: HTML - Size: 102 MB - Last synced: 22 days ago - Pushed: 23 days ago - Stars: 19 - Forks: 3

charmlab/mace

Model Agnostic Counterfactual Explanations

Language: Python - Size: 3 MB - Last synced: 1 day ago - Pushed: over 1 year ago - Stars: 84 - Forks: 12

nredell/ShapML.jl

A Julia package for interpretable machine learning with stochastic Shapley values

Language: Julia - Size: 529 KB - Last synced: 6 days ago - Pushed: 9 days ago - Stars: 80 - Forks: 7

Montimage/maip

Montimage AI Platform (MAIP) provides users with easy access to AI services developed by Montimage, through a friendly and intuitive interface.

Language: PureBasic - Size: 179 MB - Last synced: 28 days ago - Pushed: 30 days ago - Stars: 6 - Forks: 2

ncaptier/radshap

A radiomic interpretation tool based on Shapley values

Language: Python - Size: 2.88 MB - Last synced: 19 days ago - Pushed: 20 days ago - Stars: 0 - Forks: 0

hbaniecki/adversarial-explainable-ai

💡 Adversarial attacks on explanations and how to defend them

Size: 2.5 MB - Last synced: 1 day ago - Pushed: 2 months ago - Stars: 281 - Forks: 41

UVA-MLSys/gpce-covid

Interpreting County-Level COVID-19 Infections using Transformer and Deep Learning Time Series Models

Language: Jupyter Notebook - Size: 339 MB - Last synced: 1 day ago - Pushed: 1 day ago - Stars: 0 - Forks: 1

11301858/XAISuite

XAISuite: Train machine learning models, generate explanations, and compare different explanation systems with just a simple line of code.

Language: Python - Size: 15.3 MB - Last synced: 24 days ago - Pushed: 24 days ago - Stars: 5 - Forks: 1

futianfan/PEARL

deep prototype learning for EHR data

Language: Python - Size: 3.52 MB - Last synced: 24 days ago - Pushed: 10 months ago - Stars: 3 - Forks: 0

interpretml/interpret

Fit interpretable models. Explain blackbox machine learning.

Language: C++ - Size: 13.6 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 5,979 - Forks: 706

pietrobarbiero/pytorch_explain

PyTorch Explain: Interpretable Deep Learning in Python.

Language: Jupyter Notebook - Size: 42.1 MB - Last synced: 25 days ago - Pushed: about 2 months ago - Stars: 127 - Forks: 10

nemat-al/Advance_Machine_Leanring_Technologies

Tasks for Advanced Machine Learning Technologies Course @ ITMO University.

Language: Jupyter Notebook - Size: 4.47 MB - Last synced: 25 days ago - Pushed: 26 days ago - Stars: 0 - Forks: 0

12wang3/mllp

The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".

Language: Python - Size: 3.69 MB - Last synced: 27 days ago - Pushed: 2 months ago - Stars: 19 - Forks: 6

i6092467/semi-supervised-multiview-cbm

Concept bottleneck models for multiview data with incomplete concept sets

Language: Python - Size: 100 MB - Last synced: 29 days ago - Pushed: 6 months ago - Stars: 6 - Forks: 0

cair/convolutional-tsetlin-machine-tutorial

Tutorial on the Convolutional Tsetlin Machine

Language: Python - Size: 316 KB - Last synced: about 1 month ago - Pushed: over 3 years ago - Stars: 52 - Forks: 13

rd20karim/M2T-Interpretable

Official Implementation of the paper guided attention for interpretable motion captioning

Language: Python - Size: 3.15 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 3 - Forks: 0

SinaMohseni/Awesome-XAI-Evaluation

Reference tables to introduce and organize evaluation methods and measures for explainable machine learning systems

Size: 251 KB - Last synced: 3 days ago - Pushed: about 2 years ago - Stars: 74 - Forks: 9

andresilvapimentel/endocrine-disruption-explainer

Endocrine Disruption Explainer is a code to generate structural alerts of endocrine disruption of chemcial compounds using Local Interpretable Model-Agnostic Explanations (LIME) of machine learning models from TOX-21, EDC, and EDKB-FDA datasets.

Language: Jupyter Notebook - Size: 9.49 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 0 - Forks: 0

andreysharapov/xaience

All about explainable AI, algorithmic fairness and more

Language: HTML - Size: 7.81 GB - Last synced: 27 days ago - Pushed: 8 months ago - Stars: 106 - Forks: 12

ModelOriented/modelStudio

📍 Interactive Studio for Explanatory Model Analysis

Language: R - Size: 36.2 MB - Last synced: 14 days ago - Pushed: 9 months ago - Stars: 319 - Forks: 32

bgreenwell/fastshap

Fast approximate Shapley values in R

Language: R - Size: 99.4 MB - Last synced: 27 days ago - Pushed: 3 months ago - Stars: 111 - Forks: 18

BioroboticsLab/IBA

Information Bottlenecks for Attribution

Language: Python - Size: 201 KB - Last synced: 29 days ago - Pushed: over 1 year ago - Stars: 70 - Forks: 9

salesforce/ETSformer

PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

Language: Python - Size: 459 KB - Last synced: about 1 month ago - Pushed: over 1 year ago - Stars: 233 - Forks: 36

CLIAgroup/TesNet

ICCV2021 paper: Interpretable Image Recognition by Constructing Transparent Embedding Space (TesNet)

Language: Python - Size: 854 KB - Last synced: about 1 month ago - Pushed: about 2 months ago - Stars: 0 - Forks: 0

andresilvapimentel/bbbp-explainer

BBBP Explainer is a code to generate structural alerts of blood-brain barrier penetrating and non-penetrating drugs using Local Interpretable Model-Agnostic Explanations (LIME) of machine learning models from BBBP dataset.

Language: Jupyter Notebook - Size: 18.4 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 2 - Forks: 0

riccardocadei/pycre Fork of NSAPH-Software/pycre

Python implementation of Causal Rule Ensemble algorithm.

Language: Python - Size: 472 KB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 0 - Forks: 0

JonathanCrabbe/Label-Free-XAI

This repository contains the implementation of Label-Free XAI, a new framework to adapt explanation methods to unsupervised models. For more details, please read our ICML 2022 paper: 'Label-Free Explainability for Unsupervised Models'.

Language: Python - Size: 8.19 MB - Last synced: 1 day ago - Pushed: over 1 year ago - Stars: 22 - Forks: 9

firmai/ml-fairness-framework

FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)

Language: Jupyter Notebook - Size: 10.5 MB - Last synced: 13 days ago - Pushed: over 2 years ago - Stars: 68 - Forks: 14

ChristopherSwader/ICRegress

Interpretable Configurational Regression: An R Package

Language: R - Size: 1.05 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 1 - Forks: 0

utwente-dmb/xai-papers

Language: TypeScript - Size: 147 MB - Last synced: 27 days ago - Pushed: 6 months ago - Stars: 12 - Forks: 6

AIML-MED/CAPE

[CVPR 2024] CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation

Size: 2.93 KB - Last synced: about 2 months ago - Pushed: about 2 months ago - Stars: 1 - Forks: 0

jphall663/interpretable_machine_learning_with_python

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Language: Jupyter Notebook - Size: 34.7 MB - Last synced: 27 days ago - Pushed: about 1 year ago - Stars: 660 - Forks: 230

EloiZ/awesome_explainable_driving

A curated list of papers on explainability and interpretability of self-driving models

Size: 3.91 KB - Last synced: about 1 month ago - Pushed: over 3 years ago - Stars: 6 - Forks: 0

MissTiny/partially-interpretable-estimators

Language: R - Size: 301 MB - Last synced: about 2 months ago - Pushed: about 2 years ago - Stars: 1 - Forks: 0

CamBish/KINECAL-Fall-Risk-Assessment

An interpretable machine learning approach to sway-metric based fall-risk assessment. For Queen's University's ELEC 872 (AI and Intelligent Systems) final project.

Language: Jupyter Notebook - Size: 1.02 MB - Last synced: about 2 months ago - Pushed: about 2 months ago - Stars: 2 - Forks: 1

NISL-MSU/ResponsivityAnalysis

Counterfactual explanations for the identification of the features with the highest relevance on the shape of response curves generated by neural network black boxes

Language: Python - Size: 112 MB - Last synced: about 2 months ago - Pushed: about 2 months ago - Stars: 1 - Forks: 1

MarcelRobeer/explabox

Explore/examine/explain/expose your model with the explabox!

Language: Python - Size: 2.66 MB - Last synced: 26 days ago - Pushed: about 2 months ago - Stars: 12 - Forks: 0

yuyay/gpx

Official implementation of GPX: Gaussian Process Regression with Interpretable Sample-wise Feature Weights (published on TNNLS)

Language: Jupyter Notebook - Size: 81.1 KB - Last synced: about 2 months ago - Pushed: over 2 years ago - Stars: 14 - Forks: 0

Crisp-Unimib/ContrXT

a tool for comparing the predictions of any text classifiers

Language: Python - Size: 6.4 MB - Last synced: 3 days ago - Pushed: almost 2 years ago - Stars: 24 - Forks: 2

tlverse/causalglm

Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning

Language: R - Size: 7.27 MB - Last synced: about 2 months ago - Pushed: about 2 years ago - Stars: 17 - Forks: 0

pbiecek/XAIatERUM2020

Workshop: Explanation and exploration of machine learning models with R and DALEX at eRum 2020

Language: R - Size: 64.5 MB - Last synced: 14 days ago - Pushed: over 2 years ago - Stars: 52 - Forks: 11

avani17101/CD

Code for paper "Concept Distillation: Leveraging Human-Centered Explanations for Model Improvement​", Neurips 2023

Language: Python - Size: 3.97 MB - Last synced: about 2 months ago - Pushed: about 2 months ago - Stars: 2 - Forks: 0

fbargaglistoffi/BCF-IV

Package for heterogeneous causal effects in the presence of imperfect compliance (e.g., instrumental variables, fuzzy regression discontinuity designs)

Language: R - Size: 1.45 MB - Last synced: 2 months ago - Pushed: 2 months ago - Stars: 13 - Forks: 3

12wang3/rrl

The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Classification"

Language: Python - Size: 561 KB - Last synced: 2 months ago - Pushed: 2 months ago - Stars: 84 - Forks: 22

AGiannoutsos/Credit_Risk_ML_explainability

Investigating Machine Learning explainability in credit risk models by utilising LIME and DiCE methods

Size: 17.1 MB - Last synced: 2 months ago - Pushed: 2 months ago - Stars: 0 - Forks: 0

matteobrv/ma_thesis

Understanding Morphosyntactic Representations in Pretrained Language Models.

Language: Python - Size: 18.7 MB - Last synced: 2 months ago - Pushed: 2 months ago - Stars: 0 - Forks: 0

daikikatsuragawa/awesome-counterfactual-explanations

This repository is a curated collection of information (keywords, papers, libraries, books, etc.) about counterfactual explanations🙃

Size: 12.7 KB - Last synced: 2 days ago - Pushed: over 1 year ago - Stars: 10 - Forks: 0

gully/blase

Interpretable Machine Learning for astronomical spectroscopy in PyTorch and JAX

Language: Jupyter Notebook - Size: 28.9 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 23 - Forks: 6

MarekWadinger/adaptive-interpretable-ad

Self-Supervised Adaptive and Interpretable Anomaly Detection with Dynamic Operating Limits

Language: Python - Size: 158 MB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 2 - Forks: 0

Davide-Ettori/XAI_Research-Explainable-Neural-Networks

Research on various XAI methods: NAM, SHAP, EBM and Adversarial Attack

Language: Jupyter Notebook - Size: 4.66 MB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 0 - Forks: 0

Graph-COM/GSAT

[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.

Language: Jupyter Notebook - Size: 1.57 MB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 133 - Forks: 15

OptiMaL-PSE-Lab/EvalRetro

A repository for evaluating single-step retrosynthesis algorithms

Language: Python - Size: 1.3 GB - Last synced: 22 days ago - Pushed: about 1 month ago - Stars: 9 - Forks: 1

innoisys/EPU-CNN

Official Implementation of "E pluribus unum interpretable convolutional neural networks"

Language: Python - Size: 910 KB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 5 - Forks: 0

mdhabibi/Transparent-Malaria-Detection-CNN-CAM-LIME

Enhanced CNN model for malaria cell classification featuring Class Activation Mapping (CAM) for anomaly localization and LIME for interpretability, ensuring high accuracy and transparent AI diagnostics.

Language: Jupyter Notebook - Size: 24.6 MB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 4 - Forks: 0

nredell/shapFlex

An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model

Language: R - Size: 2.13 MB - Last synced: 27 days ago - Pushed: almost 4 years ago - Stars: 70 - Forks: 7

h2oai/mli-resources

H2O.ai Machine Learning Interpretability Resources

Language: Jupyter Notebook - Size: 65.8 MB - Last synced: 3 months ago - Pushed: over 3 years ago - Stars: 477 - Forks: 134

XAI-Demonstrator/visualime

Implementation of LIME focused on producing user-centric local explanations for image classifiers.

Language: Python - Size: 157 KB - Last synced: 14 days ago - Pushed: 15 days ago - Stars: 6 - Forks: 1

M-Nauta/PIPNet

PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)

Language: Python - Size: 3.85 MB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 43 - Forks: 8

imatge-upc/SurvLIMEpy

Local interpretability for survival models

Language: Python - Size: 3.69 MB - Last synced: 29 days ago - Pushed: 5 months ago - Stars: 17 - Forks: 4

kenza-ily/24UCL_comp0195-RAI

Accountable, Transparent, and Responsible AI | UCL COMP0195

Language: Jupyter Notebook - Size: 22.2 MB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 0 - Forks: 0

sumny/eagga

Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models

Language: R - Size: 4.64 MB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 1 - Forks: 0

SergeiAP/advanced-analytics-process-control

Creating the model and approach to manage and adjust the process/equipment

Language: Jupyter Notebook - Size: 8.4 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 0 - Forks: 0

Klest94/Bellatrex

Building Explanations through a LocaLly AccuraTe Rule EXtractor

Language: Jupyter Notebook - Size: 212 MB - Last synced: 27 days ago - Pushed: 27 days ago - Stars: 5 - Forks: 1

JHoelli/Awesome-Time-Series-Explainability

A list of (post-hoc) XAI for time series

Size: 356 KB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 12 - Forks: 3

RishiDarkDevil/daam-i2i Fork of castorini/daam

Diffusion attentive attribution maps for interpreting Stable Diffusion for image-to-image attention.

Language: Python - Size: 30.3 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 29 - Forks: 0

jyhong0304/concept_centric_transformers

The official implementation of Concept-Centric Transformers (Hong et al., WACV 2024).

Language: Python - Size: 14.2 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 3 - Forks: 2

mfumagalli68/xi-method

Xi method

Language: Python - Size: 2.82 MB - Last synced: 13 days ago - Pushed: 8 months ago - Stars: 5 - Forks: 0

adaamko/POTATO

XAI based human-in-the-loop framework for automatic rule-learning.

Language: Jupyter Notebook - Size: 6.07 MB - Last synced: 12 days ago - Pushed: 9 months ago - Stars: 46 - Forks: 8

M-Nauta/ProtoTree

ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

Language: Python - Size: 870 KB - Last synced: 3 months ago - Pushed: almost 2 years ago - Stars: 82 - Forks: 16

annabelleluo/HELOC

This is the HKU STAT3612 project, 2020. This is an interpretable machine learning project for credit scoring with Home Equity Line of Credit data.

Language: Jupyter Notebook - Size: 5.9 MB - Last synced: 4 months ago - Pushed: about 1 year ago - Stars: 1 - Forks: 0

emmachollet/ComparSDMsQuantifOverfitSuppInterpr_DataPackage

Package with data, scripts and plots for manuscript "A comparison of machine learning and statistical species distribution models: when overfitting hurts interpretation" (submitted to Ecological Modelling, Dec 2022)

Language: R - Size: 290 MB - Last synced: 4 months ago - Pushed: 5 months ago - Stars: 4 - Forks: 1

KewKalustian/Spotify_COVID-19_DACH

Article repository

Language: R - Size: 49.9 MB - Last synced: 4 months ago - Pushed: over 2 years ago - Stars: 0 - Forks: 1

andresilvapimentel/mutagen-explainer

Mutagen Explainer is a code to generate structural alerts of mutagenicity of chemcial compounds using Local Interpretable Model-Agnostic Explanations (LIME) of machine learning models from Bursi and Hansen Ames mutagenicity datasets.

Language: Jupyter Notebook - Size: 16.4 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 0 - Forks: 0

idealo/cnn-exposed

🕵️‍♂️ Interpreting Convolutional Neural Network (CNN) Results.

Language: Jupyter Notebook - Size: 88 MB - Last synced: 3 months ago - Pushed: about 5 years ago - Stars: 175 - Forks: 29