With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js. Learn more →
Lime Alternatives
Similar projects and alternatives to lime
-
-
eli5
A library for debugging/inspecting machine learning classifiers and explaining their predictions
-
SurveyJS
Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.
-
-
Fruit-Images-Dataset
Fruits-360: A dataset of images containing fruits and vegetables
-
Cause-of-decision-in-Swahili-sentiments
This repository special to demonstrate the cause of decision or explainability on classifying Swahili sentiments as a data professional for business needs.
-
shap
Discontinued A game theoretic approach to explain the output of any machine learning model. [Moved to: https://github.com/shap/shap] (by slundberg)
lime reviews and mentions
-
Ethical and Bias Testing in Generative AI: A Practical Guide to Ensuring Ethical Conduct with Test Cases and Tools
Other tools like Fairness Indicators, Lime, and SHAP are also valuable resources for ethical and bias testing.
-
Model interpretation with many features
https://github.com/slundberg/shap this or https://github.com/marcotcr/lime would be relevant to you, especially if you want to look at explaining a single prediction.
-
The cause of a decision in Swahili social media sentiments
In today's article, I will work with you through building a machine learning model for Swahili social media sentiment classification with the interpretability of each prediction of our final model using Local Interpretable Model-Agnostic Explanations.
-
Cause of overfitting using vgg16 transfer learning
Or you could see what activates miss-classified labels (e.g. with LIME https://github.com/marcotcr/lime) and try to understand if there are some common causes (e.g. reflection, different lighting, background etc.).
-
[Q] What's the community's opinion of "interpretable ML/AI"?
LIME (https://github.com/marcotcr/lime) and Anchor (https://github.com/marcotcr/anchor), both by Marco Tulio Ribeiro (https://homes.cs.washington.edu/~marcotcr/).
-
How to extract keywords important to a text classification problem?
If the PCA is needed, you can also use a black box explainer, like lime: https://github.com/marcotcr/lime
-
How an ML algorithm shows which aspect of a comparison contributes more to the result?
LIME basically builds a bunch of really small linear models. It makes the assumption that although a model may be very complex overall, it can be locally be represented through linear relationships. LIME builds these linear models by picking a point and changing the data ever so slightly. Again, a good python implementation and more details can be found here.
-
A note from our sponsor - SurveyJS
surveyjs.io | 28 Mar 2024
Stats
marcotcr/lime is an open source project licensed under BSD 2-clause "Simplified" License which is an OSI approved license.
The primary programming language of lime is JavaScript.