📺 A Python library for pruning and visualizing Keras Neural Networks' structure and weights
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Updated
Dec 24, 2019 - Python
📺 A Python library for pruning and visualizing Keras Neural Networks' structure and weights
XAI - An eXplainability toolbox for machine learning
Official implementation of GPX: Gaussian Process Regression with Interpretable Sample-wise Feature Weights (published on TNNLS)
XAI approaches based on the TensorFlow framework to understand neural networks decision
a tool for comparing the predictions of any text classifiers
Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curve.
A python library to agnostically explain multi-label black-box classifiers (tabular data)
A scoring system for explainability
Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework
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.
ibreakdown is model agnostic predictions explainer with interactions support, library can show contribution of each feature of your prediction value
CLI for XAISuite Library
Block code for the XAISuite library: 11301858.github.io/xaisuiteweb
The NLP Bias Identification Toolkit
Xi method
Fast and incremental explanations for online machine learning models. Works best with the river framework.
A Python package with explanation methods for extraction of feature interactions from predictive models
This repository contains the code for the XAIInferencerEngine PyPi library.
XAI for yoloV8
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