Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
#计算机科学#XAI - An eXplainability toolbox for machine learning
#计算机科学#Neural network visualization toolkit for tf.keras
#计算机科学#Fast and incremental explanations for online machine learning models. Works best with the river framework.
Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework
TrustyAI Explainability Toolkit
#自然语言处理#The NLP Bias Identification Toolkit
#计算机科学#A Python package with explanation methods for extraction of feature interactions from predictive models
#自然语言处理#a tool for comparing the predictions of any text classifiers
#计算机科学#Official implementation of GPX: Gaussian Process Regression with Interpretable Sample-wise Feature Weights (published on TNNLS)
Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curve.
An XAI library that helps to explain AI models in a really quick & easy way
📺 A Python library for pruning and visualizing Keras Neural Networks' structure and weights
#计算机科学#A model-agnostic library for generating explanations of machine learning predictions, supporting diverse XAI methods like CEM and LIME.
Model-agnostic Statistical/Machine Learning explainability (currently Python) for tabular data
A python library to agnostically explain multi-label black-box classifiers (tabular data)
#计算机科学#XAISuite: Train machine learning models, generate explanations, and compare different explanation systems with just a simple line of code.
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 ele...
