ALEPython
Model explainer
An ALE plot generation tool for explaining machine learning model predictions
Python Accumulated Local Effects package
158 stars
10 watching
42 forks
Language: Python
last commit: over 1 year ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 pbiecek/xaiaterum2020 | An R package and workshop materials for explaining machine learning models using explainable AI techniques | 52 |
 interpretml/dice | Provides counterfactual explanations for machine learning models to facilitate interpretability and understanding. | 1,364 |
 blobcity/autoai | A Python-based framework for automating the process of finding and training the best-performing machine learning model for regression and classification tasks on numerical data. | 174 |
 sergioburdisso/pyss3 | A Python package implementing an interpretable machine learning model for text classification with visualization tools | 336 |
 minglllli/cbafed | A PyTorch implementation of a method for improving semi-supervised learning in federated settings by adapting pseudo labels to balance classes. | 7 |
 modeloriented/dalex | A tool to help understand and explain the behavior of complex machine learning models | 1,375 |
 neulab/explainaboard | An interactive tool to analyze and compare the performance of natural language processing models | 361 |
 thomasp85/lime | An R package for providing explanations of predictions made by black box classifiers. | 485 |
 lge-arc-advancedai/auptimizer | Automates model building and deployment process by optimizing hyperparameters and compressing models for edge computing. | 200 |
 allenai/scibert | A BERT model trained on scientific text for natural language processing tasks | 1,521 |
| allenai/olmo-eval | An evaluation framework for large language models. | 310 |
 project-dc/pygeneses | A PyTorch-based framework for training and studying artificial species in bio-inspired environments | 72 |
 jacobgil/pytorch-explain-black-box | A PyTorch implementation of a method to explain the decisions made by deep learning models on image classification tasks | 334 |
 ethicalml/xai | An eXplainability toolbox for machine learning that enables data analysis and model evaluation to mitigate biases and improve performance | 1,125 |
 marcelrobeer/explabox | An exploratory tool for analyzing and understanding machine learning models | 15 |