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What’s Wrong with LIME

Towards Data Science

Local Interpretable Model-agnostic Explanations (LIME) is a popular Python package for explaining individual model’s predictions for text classifiers or classifiers that act on tables (NumPy arrays…

Understanding LIME

Towards Data Science

Local Interpretable Model-agnostic Explanations (LIME) is a Python project developed by Ribeiro et al. [1] to interpret the predictions of any supervised Machine Learning (ML) model. Most ML…

A Deep Dive on LIME for Local Interpretations

Towards Data Science

LIME is the OG of XAI methods. It allows us to understand how machine learning models work. Specifically, it can help us understand how individual predictions are made (i.e. local interpretations).

Squeezing LIME in a custom network

Towards Data Science

Machine and deep learning models are applied in a wide range of areas, spanning from fundamental research to industries and services. Their successful application to a wide diversity of problems has…

Instability of LIME explanations

Towards Data Science

In this article, I’d like to go very specific on the LIME framework for explaining machine learning predictions. I already covered the description of the method in this article, in which I also gave…

Squeezing More out of LIME with Python

Towards Data Science

How to create global aggregations of LIME weights Continue reading on Towards Data Science

Unboxing the black box using LIME

Towards Data Science

As the complexity of a model increases, its accuracy increases but its interpretability reduces. Most of the complex machine learning models that are math-heavy are not easily interpretable and run…

Understanding how LIME explains predictions

Towards Data Science

In a recent post I introduced three existing approaches to explain individual predictions of any machine learning model. In this post I will focus on one of them: Local Interpretable Model-agnostic…

Idea Behind LIME and SHAP

Towards Data Science

In machine learning, there has been a trade-off between model complexity and model performance. Complex machine learning models e.g. deep learning (that perform better than interpretable models e.g…

Corona JS

Analytics Vidhya

Why outbreaks like coronavirus spread exponentially, and how to “flatten the curve”. Social Distancing is the way, and we're doing it right.

ML Model Interpretability — LIME

Analytics Vidhya

Lime is short for Local Interpretable Model-Agnostic Explanations. Each part of the name reflects something that we desire in explanations. Local refers to local fidelity i.e "around" the instance bei...

Spark

Towards Data Science

Shilpa, a rookie data scientist, was in love with her first job with a budding startup: an AI-based Fintech innovation hub. While the startup started with the traditional single machine, vertical…