feature-importance · GitHub Topics

pytorch / captum

Model interpretability and understanding for PyTorch

翻译 - PyTorch的模型可解释性和理解

interpretability interpretable-ai interpretable-ml feature-importance feature-attribution

Python 5.11 k

7 天前

EthicalML / xai

#计算机科学#XAI - An eXplainability toolbox for machine learning

explainability xai 机器学习人工智能 bias explainable-ai explainable-ml interpretability xai-library evaluation upsampling feature-importance

Python 1.16 k

3 年前

aerdem4 / lofo-importance

#计算机科学#Leave One Feature Out Importance

feature-importance 机器学习数据科学 feature-selection explainable-ai

Python 827

1 个月前

duxuhao / Feature-Selection

#计算机科学#Features selector based on the self selected-algorithm, loss function and validation method

机器学习 feature-engineering feature-selection 数据科学 feature-importance feature-extraction

Python 675

6 年前

kochlisGit / ProphitBet-Soccer-Bets-Predictor

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...

soccer 统计深度神经网络 feature-importance 机器学习神经网络 random-forest soccer-matches football-data 数据可视化 pandas-dataframe seaborn optuna

Python 384

1 个月前

dominance-analysis / dominance-analysis

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...

regression-models logistic-regression predictor classification-model feature-engineering feature-selection feature-importance

Python 160

2 年前

archd3sai / Predictive-Maintenance-of-Aircraft-Engine

In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbofan engine.

regression classification cnn-keras feature-importance

Jupyter Notebook 145

3 年前

csinva / hierarchical-dnn-interpretations

#计算机科学#Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

interpretability 神经网络机器学习 convolutional-neural-networks PyTorch explainability 深度学习 explainable-ai 人工智能 Python 数据科学 Jupyter Notebook 深度神经网络统计 feature-importance iclr

Jupyter Notebook 128

4 年前

laura-rieger / deep-explanation-penalization

#计算机科学#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

interpretability 神经网络机器学习 convolutional-neural-network PyTorch explainability 深度学习 explainable-ai 人工智能 Python 数据科学 Jupyter Notebook feature-importance recurrent-neural-network fairness fairness-ml interpretable-deep-learning

Jupyter Notebook 127

4 年前

sylvaticus / BetaML.jl

#计算机科学#Beta Machine Learning Toolkit

机器学习 neural-networks clustering 数据科学深度学习 regression classification decision-trees Julia 语言 pca random-forest 人工智能 feature-importance autoencoder

Julia 98

2 个月前

nredell / ShapML.jl

A Julia package for interpretable machine learning with stochastic Shapley values

shap interpretable-machine-learning feature-importance Julia 语言 shapley

Julia 92

10 个月前

nredell / shapFlex

#计算机科学#An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model

shapley ensemble 机器学习 package R feature-importance interpretable-machine-learning r-package shap causality causal-inference causal-networks

R 74

5 年前

YousefGh / kmeans-feature-importance

Adding feature_importances_ property to sklearn.cluster.KMeans class

feature-importance interpretability keyword-extraction

Jupyter Notebook 64

2 年前

mlpapers / feature-selection

#Awesome#Awesome papers on Feature Selection

feature-selection feature-importance correlation dimensionality-reduction Awesome Lists

1 年前

isarn / isarn-sketches-spark

#数据仓库#Routines and data structures for using isarn-sketches idiomatically in Apache Spark

Apache Spark Scala aggregator dataset 数据集 dataframe dataframes Python feature-importance pyspark spark-ml

Scala 29

9 个月前

rebelosa / feature-importance-neural-networks

#计算机科学#Variance-based Feature Importance in Neural Networks

neural-networks feature-importance 深度学习

Jupyter Notebook 28

5 年前

mattiacarletti / DIFFI

Official repository of the paper "Interpretable Anomaly Detection with DIFFI: Depth-based Isolation Forest Feature Importance", M. Carletti, M. Terzi, G. A. Susto.

anomaly-detection feature-importance

Jupyter Notebook 28

7 个月前

csinva / disentangled-attribution-curves

#计算机科学#Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"

interpretability 机器学习 scikit-learn Python 统计 explainable-ai 人工智能 stats random-forest feature-importance feature-engineering

Python 27

4 年前

unnir / CancelOut

#计算机科学#CancelOut is a special layer for deep neural networks that can help identify a subset of relevant input features for streaming or static data.

深度学习 feature-selection feature-importance

Jupyter Notebook 26

4 年前

JonathanCrabbe / Simplex

#计算机科学#This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help of a corpus of examples. For more details, please read our Neur...

机器学习人工智能 explainable-ai latent-space interpretability method feature-importance neurips-2021 neurips neural-networks

Python 24

2 年前