slundberg / shap

A game theoretic approach to explain the output of any machine learning model.

machine-learning deep-learning gradient-boosting interpretability shapley shap explainability

Updated Aug 19, 2020
Jupyter Notebook

oegedijk / explainerdashboard

explainerdashboard is a python package for generating analytical dashboards that explain the inner workings of so-called "blackbox" machine learning models.

dashboard plotly dash data-scientists model-predictions interactive-plots interactive-dashboards xai inner-workings shap explainer xai-library shap-values permutation-importances

Updated Jul 24, 2020
Jupyter Notebook

nredell / ShapML.jl

Star

A Julia package for interpretable machine learning with stochastic Shapley values

julia feature-importance shapley interpretable-machine-learning iml shap shapley-value stochastic-shapley-values

Updated Jul 10, 2020
Julia

dylan-slack / Fooling-LIME-SHAP

Star

Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)

machine-learning paper lime interpretability adversarial-attacks explanations shap post-hoc-explanation fool-lime

Updated Jun 12, 2020
Jupyter Notebook

chaitjo / working-women

Star

Code for the paper 'Working Women and Caste in India' (ICLR 2019 AI for Social Good Workshop)

machine-learning women india social-good gradient-boosting interpretability shap caste

Updated Feb 12, 2020
Jupyter Notebook

nredell / shapFlex

Star

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

package machine-learning r ensemble r-package causality causal-inference feature-importance causal-networks shapley interpretable-machine-learning iml shap shapley-value shapley-values

Updated Jun 9, 2020
R

PrashantSaikia / Dynamic-SHAP-Plots

Star

Enabling interactive plotting of the visualizations from the SHAP project.

visualization machine-learning deep-learning plotly data-visualization visualization-library interactive-visualizations interpretability visualization-tools interpretable-deep-learning plotly-analytics-projects interpretable-machine-learning shap

Updated Jan 15, 2020
Python

BBloggsbott / masters-chance-of-admit

Star

Open

Add minimum chance required for universities

6

BBloggsbott commented Mar 25, 2019

Users don't know what chance they need to get into universities of their choice.

Minimum chance neede to get into some top universities.

Feature originally suggested by naveen_v on fastai forums

rodrigobressan / keras_boston_housing_price

Star

Keras 101: A simple Neural Network for House Pricing regression

keras jupyter-notebook boston-housing-price-prediction model-explanation shap

Updated Oct 8, 2019
Jupyter Notebook

rezacsedu / OncoNetExplainer

Star

OncoNetExplainer: Explainable Prediction of Cancer Types Based on Gene Expression Data

cnn cancer-genomics feature-importance gradcam gradient-boosted-trees shap cancer-type-prediction

Updated Apr 27, 2020
Jupyter Notebook

takumiw / Deep-Learning-for-Human-Activity-Recognition

Star

The task of human activity recognition (HAR) is implemented by using smartphones sensor dataset and LightBGM, CNN, and LSTM.

machine-learning deep-learning keras classification lightgbm human-activity-recognition convolutional-neural-network smartphone-sensor-data shap

Updated Jun 2, 2020
Jupyter Notebook

rdolor / research-collections

Star

Contains a collection of my experimentations, explorations, and data analysis of random datasets

exploratory-data-analysis pca kmeans rtb graph-clustering shap model-retraining

Updated Oct 22, 2019
HTML

viniaraujoo / deepinterpretability

Star

Interpretability of Image Keras Models

machine-learning deep-learning keras lime keras-tensorflow interpretability xai shap

Updated Oct 27, 2019
Python

amod99 / Shap_Demo

Star

Demo of shapely values for interpreting decision tree model

regression xgboost shapely shap

Updated Dec 25, 2019
Jupyter Notebook

yoonslab / omelet

Star

AutoML + XAI + mlflow

data h2o profiling automl xai mlflow shap

Updated May 21, 2020
HTML

TannerGilbert / Model-Interpretation

Star

Overview of different model interpretability libraries.

lime model-interpretation shap model-interpretability captum tf-explain

Updated Jul 30, 2020
Jupyter Notebook

chengning-zhang / Simple-TAN-and-Ensemble-TAN

Star

Bayesian network implementation API inspired by SciKit-learn.

scikit-learn bayesian-network shap ensemble-tan

Updated Apr 8, 2020
Jupyter Notebook

bipinkc19 / explaining-black-boxes

Star

Explaining complex ML models

nlp prediction lime vizualisation shap explaining-black-boxes

Updated Sep 16, 2019
Jupyter Notebook

dainst / wordpress-storytelling

Star

Wordpress Plugin to embed (epigraphic) Content into posts by just pasting URLs

wordpress wordpress-plugin shap

Updated Feb 15, 2019
XSLT

XiaoqiMa / shapSD

Star

Explain variable influence in black-box model through pattern mining

pattern-mining explainable-ai shap

Updated Dec 9, 2019
Python

tommartensen / tic

Star

TIC is a library that acts as a Toolbox for Interpretability Comparison.

lime interpretability shap complexity-faithfulness-graph

Updated Oct 10, 2019
Python

nataberishvili / nataberishvili.github.io

Star

python science data dplyr h2o datascience randomforest machinelearning loan-default-prediction medicare-data binaryclassification shap exploratorydataanalysis berishvili ggplo2

Updated Aug 11, 2020

TmLev / interpretable-ml

Star

Article on the interpretability of ML models

machine-learning dash lime shap

Updated Jun 25, 2020
Python

asgaardlab / done-20-markos-dota2_win_prediction-code

Star

Project to investigate win prediction models for Dota 2 and factors that explain such predictions

python games random-forest artificial-intelligence xgboost dota2 predictive-modeling opendota shap

Updated Aug 6, 2020
Jupyter Notebook

AChepurnoi / cnn-interpretability

Star

Responsible datascience final project

neural-network cnn convolutional-neural-networks backpropagation lime gradcam shap

Updated May 19, 2019
Jupyter Notebook

thadaJ / autoInsight

Star

Library for displaying insight of data automatically

xgboost shap

Updated Nov 20, 2019
Jupyter Notebook

McGill-MMA-EnterpriseAnalytics / datasectuals

Star

Predicting whether or not a person deposits money after a marketing campaign. Gain insights to develop the best strategy in the next marketing campaign

modeling prescriptive-analytics predictive-analytics pandas-profiling automl shap marketing-campaign

Updated Feb 24, 2020
Jupyter Notebook

dainst / wordpress-components

Star

Main repository containing all wordpress templates and plugins developed at the DAI.

docker wordpress shap

Updated Nov 1, 2019
PHP

coxevti / instagram-week-7-backend

Star

Semana omniStack 7.0 #rocketseat [ back-end ]

nodejs cors mongo express mongodb socket-io multer shap

Updated Jul 17, 2020
JavaScript

dainst / wordpress-shap-theme

Star

a DUMMY for the SHAB theme wich will be there

wordpress wordpress-theme shap

Updated Jun 17, 2019
CSS

shap

Here are 47 public repositories matching this topic...

slundberg / shap

oegedijk / explainerdashboard

nredell / ShapML.jl

dylan-slack / Fooling-LIME-SHAP

chaitjo / working-women

nredell / shapFlex

PrashantSaikia / Dynamic-SHAP-Plots

BBloggsbott / masters-chance-of-admit

Add minimum chance required for universities

rodrigobressan / keras_boston_housing_price

rezacsedu / OncoNetExplainer

takumiw / Deep-Learning-for-Human-Activity-Recognition

rdolor / research-collections

viniaraujoo / deepinterpretability

amod99 / Shap_Demo

yoonslab / omelet

TannerGilbert / Model-Interpretation

chengning-zhang / Simple-TAN-and-Ensemble-TAN

bipinkc19 / explaining-black-boxes

dainst / wordpress-storytelling

XiaoqiMa / shapSD

tommartensen / tic

nataberishvili / nataberishvili.github.io

TmLev / interpretable-ml

asgaardlab / done-20-markos-dota2_win_prediction-code

AChepurnoi / cnn-interpretability

thadaJ / autoInsight

McGill-MMA-EnterpriseAnalytics / datasectuals

dainst / wordpress-components

coxevti / instagram-week-7-backend

dainst / wordpress-shap-theme

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