This project uses XAI to make AI-based Alzheimer's predictions understandable for doctors, aiming to improve diagnosis & treatment for patients
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Updated
Apr 4, 2024 - Python
This project uses XAI to make AI-based Alzheimer's predictions understandable for doctors, aiming to improve diagnosis & treatment for patients
This repository contains the code for the XAIInferencerEngine PyPi library.
Block code for the XAISuite library: 11301858.github.io/xaisuiteweb
XAI approaches based on the TensorFlow framework to understand neural networks decision
A scoring system for explainability
CLI for XAISuite Library
ibreakdown is model agnostic predictions explainer with interactions support, library can show contribution of each feature of your prediction value
Xi method
Artificial Neural Networks for Java This package provides Object oriented Neural Networks for making Explainable Networks. Object Oriented Network structure is helpful for observing each and every element the model. This package is developed for XAI research and development.
XAISuite: Train machine learning models, generate explanations, and compare different explanation systems with just a simple line of code.
Model-agnostic Statistical/Machine Learning explainability (currently Python) for tabular data
XAI for yoloV8
A python library to agnostically explain multi-label black-box classifiers (tabular data)
Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curve.
📺 A Python library for pruning and visualizing Keras Neural Networks' structure and weights
A library that helps to explain AI models in a really quick & easy way
Official implementation of GPX: Gaussian Process Regression with Interpretable Sample-wise Feature Weights (published on TNNLS)
TrustyAI Explainability Toolkit
A Python package with explanation methods for extraction of feature interactions from predictive models
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