feature-importance 开源项目推荐（483 个）

meta-pytorch /captum

Model interpretability and understanding for PyTorch

EthicalML /xai

XAI——面向机器学习的可解释性工具箱

aerdem4 /lofo-importance

Leave One Feature Out Importance

mmschlk /shapiq

Shapley Values and Shapley Interactions for Machine Learning

duxuhao /Feature-Selection

Features selector based on the self selected-algorithm, loss function and validation method

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) methods. Additionally, it provides betting agents based on Deep Reinforcement Learning (DRL), which can learn optimal betting strategies.

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 resource allocation models.

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.

laura-rieger /deep-explanation-penalization

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

csinva /hierarchical-dnn-interpretations

Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

sylvaticus /BetaML.jl

Beta Machine Learning Toolkit

nredell /ShapML.jl

A Julia package for interpretable machine learning with stochastic Shapley values

nredell /shapFlex

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

YousefGh /kmeans-feature-importance

Adding feature_importances_ property to sklearn.cluster.KMeans class

mlpapers /feature-selection

Feature Selection and Variable Selection: papers and methods

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.

rebelosa /feature-importance-neural-networks

Variance-based Feature Importance in Neural Networks

isarn /isarn-sketches-spark

Routines and data structures for using isarn-sketches idiomatically in Apache Spark

teyang-lau /HDB_Resale_Prices

Predicted and identified the drivers of Singapore HDB resale prices (2015-2019) with 0.96 Rsquare & $20,000 MAE. Web app deployment using Streamlit for user price prediction.

AmirhosseinHonardoust /Customer-Churn-Prediction

Customer churn prediction with Python using synthetic datasets. Includes data generation, feature engineering, and training with Logistic Regression, Random Forest, and Gradient Boosting. Improved pipeline applies hyperparameter tuning and threshold optimization to boost recall. Outputs metrics, reports, and charts.