Topic: xai-library Goto Github
Some thing interesting about xai-library
Some thing interesting about xai-library
xai-library,XAISuite: Train machine learning models, generate explanations, and compare different explanation systems with just a simple line of code.
User: 11301858
Home Page: https://xaisuite.wordpress.com
xai-library,Block code for the XAISuite library: 11301858.github.io/xaisuiteweb
User: 11301858
Home Page: https://11301858.github.io/xaisuiteblock/
xai-library,CLI for XAISuite Library
User: 11301858
Home Page: https://11301858.github.io/xaisuiteweb
xai-library,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.
User: aatmaj-zephyr
Home Page: https://aatmaj-zephyr.github.io/ANN4j/
xai-library,The NLP Bias Identification Toolkit
Organization: biaslyze-dev
Home Page: https://biaslyze.org
xai-library,A python library to agnostically explain multi-label black-box classifiers (tabular data)
User: cecipani
xai-library,a tool for comparing the predictions of any text classifiers
User: crisp-unimib
xai-library,This project uses XAI to make AI-based Alzheimer's predictions understandable for doctors, aiming to improve diagnosis & treatment for patients
User: easyans
xai-library,XAI - An eXplainability toolbox for machine learning
Organization: ethicalml
Home Page: https://ethical.institute/principles.html#commitment-3
xai-library,ibreakdown is model agnostic predictions explainer with interactions support, library can show contribution of each feature of your prediction value
User: jettify
xai-library,Neural network visualization toolkit for tf.keras
User: keisen
Home Page: https://keisen.github.io/tf-keras-vis-docs/
xai-library,XAI approaches based on the TensorFlow framework to understand neural networks decision
User: ksoh97
xai-library,Xi method
User: mfumagalli68
xai-library,Fast and incremental explanations for online machine learning models. Works best with the river framework.
User: mmschlk
xai-library,Shapley Interactions for Machine Learning
User: mmschlk
Home Page: https://shapiq.readthedocs.io
xai-library,A scoring system for explainability
User: msetzu
xai-library,Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
User: oegedijk
Home Page: http://explainerdashboard.readthedocs.io
xai-library,A Python package with explanation methods for extraction of feature interactions from predictive models
Organization: pyartemis
xai-library,Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curve.
User: rodrigobdz
Home Page: https://pypi.org/project/lrp-pf-auc/
xai-library,XAI for yoloV8
User: spritan
Home Page: https://spritan.github.io/YOLOv8_Explainer/
xai-library,An XAI library that helps to explain AI models in a really quick & easy way
User: stavrostheocharis
xai-library,This repository contains the code for the XAIInferencerEngine PyPi library.
User: suiens
xai-library,Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework
User: szandala
Home Page: https://pypi.org/project/torchprism
xai-library,Model-agnostic Statistical/Machine Learning explainability (currently Python) for tabular data
Organization: techtonique
Home Page: https://techtonique.github.io/teller/
xai-library,TrustyAI Explainability Toolkit
Organization: trustyai-explainability
xai-library,:tv: A Python library for pruning and visualizing Keras Neural Networks' structure and weights
User: yuvalailer
xai-library,Official implementation of GPX: Gaussian Process Regression with Interpretable Sample-wise Feature Weights (published on TNNLS)
User: yuyay
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