12 results found Sort:

pytorch
captum pytorch
469
4.6k
bsd-3-clause
245
Model interpretability and understanding for PyTorch
interpretability interpretable-ai interpretable-ml feature-importance feature-attribution
Created 2019-08-27
1,092 commits to master branch, last one 16 hours ago
EthicalML
xai EthicalML
160
1.1k
mit
44
XAI - An eXplainability toolbox for machine learning
ai ml xai bias imbalance evaluation upsampling xai-library downsampling explainability explainable-ai explainable-ml bias-evaluation interpretability machine-learning feature-importance artificial-intelligence machine-learning-explainability
Created 2019-01-11
91 commits to master branch, last one 2 years ago
aerdem4
lofo-importance aerdem4
82
806
mit
14
Leave One Feature Out Importance
data-science explainable-ai machine-learning feature-selection feature-importance
Created 2019-01-14
32 commits to master branch, last one 4 months ago
kochlisGit
ProphitBet-Soccer-Bets-Predictor kochlisGit
97
271
mit
22
ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using Advanced Machine Learning (ML) m...
optuna soccer seaborn statistics predictions football-data random-forest neural-network soccer-betting soccer-matches upcoming-games feature-analysis imbalanced-learn pandas-dataframe data-visualization feature-importance imbalanced-learning deep-neural-networks interpretability-methods machine-learning-algorithms
Created 2022-03-18
212 commits to main branch, last one 25 days ago
dominance-analysis
dominance-analysis dominance-analysis
57
146
mit
20
This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal...
r-square dominance predictor keydrivers shapley-value pseudo-r-square feature-selection regression-models dominance-analysis feature-importance feature-engineering logistic-regression multiple-regression relative-importance classification-model dominance-statistics predictor-importance
Created 2018-12-05
515 commits to master branch, last one 9 months ago
csinva
hierarchical-dnn-interpretations csinva
22
124
mit
9
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
ai ml acd iclr python pytorch statistics data-science deep-learning explainability explainable-ai interpretation neural-network interpretability jupyter-notebook machine-learning feature-importance deep-neural-networks artificial-intelligence convolutional-neural-networks
Created 2018-05-18
60 commits to master branch, last one 2 years ago
archd3sai
Predictive-Maintenance-of-Aircraft-Engine archd3sai
41
124
unknown
2
In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbofan engine.
cnn-keras regression classification rul-prediction feature-importance lstm-neural-networks predictive-maintenance similarity-based-model exponential-degradation
Created 2019-05-07
50 commits to master branch, last one about a year ago
laura-rieger
deep-explanation-penalization laura-rieger
13
123
mit
10
Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584
ai ml cdep python pytorch fairness fairness-ml data-science deep-learning explainability explainable-ai neural-network interpretability jupyter-notebook machine-learning feature-importance artificial-intelligence recurrent-neural-network interpretable-deep-learning convolutional-neural-network
Created 2019-02-12
89 commits to master branch, last one 3 years ago
sylvaticus
BetaML.jl sylvaticus
13
91
mit
6
Beta Machine Learning Toolkit
ai ml pca julia clustering imputation regression autoencoder data-science deep-learning random-forest classification decision-trees neural-networks machine-learning feature-importance artificial-intelligence
Created 2020-04-08
641 commits to master branch, last one 7 days ago
nredell
ShapML.jl nredell
7
81
mit
4
A Julia package for interpretable machine learning with stochastic Shapley values
iml shap julia shapley shapley-value feature-importance stochastic-shapley-values interpretable-machine-learning
Created 2020-01-23
118 commits to master branch, last one 2 years ago
YousefGh
kmeans-feature-importance YousefGh
21
62
mit
2
Adding feature_importances_ property to sklearn.cluster.KMeans class
k-means interpretability feature-importance keyword-extraction
Created 2021-07-17
22 commits to kmeans-feature-importance-v01 branch, last one 9 months ago
mmschlk
shapiq mmschlk
3
25
mit
2
SHAP Interaction Quantification (short SHAP-IQ) is an XAI framework extending on the well-known shap explanations by introducing interactions i.e. synergy scores.
xai python xai-library visualization feature-importance feature-interactions
Created 2023-10-17
558 commits to main branch, last one 18 hours ago