Model Interpretability

Interpretable Models

Christophm Interpretable Machine Learning Book

The easiest way to achieve interpretability is to use only a subset of algorithms that create interpretable models. Linear regression, logistic regression and the decision tree are commonly used inter...

Interpretability

Christophm Interpretable Machine Learning Book

It is difficult to (mathematically) define interpretability. A (non-mathematical) definition of interpretability that I like by Miller (2017) 3 is: Interpretability is the degree to which a human can ...

InterpretML: Another Way to Explain Your Model

Towards Data Science

Interpretability can be crucial when implementing ML models. By interpreting models , customers can gain trust in the model and facilitate adoption. It may also be helpful in debugging your model…

Neural Basis Models for Interpretability

Towards Data Science

Unpacking the new interpretable model proposed by Meta AI Continue reading on Towards Data Science

Which models are interpretable?

Towards Data Science

A brief overview of some interpretable machine learning models Continue reading on Towards Data Science

Other Interpretable Models

Christophm Interpretable Machine Learning Book

The list of interpretable models is constantly growing and of unknown size. It includes simple models such as linear models, decision trees and naive Bayes, but also more complex ones that combine or ...

Interpretability of Deep Learning Models

Towards Data Science

Model Interpretability of Deep Neural Networks (DNN) has always been a limiting factor for use cases requiring explanations of the features involved in modelling and such is the case for many…

Introduction to Machine Learning Model Interpretation

Towards Data Science

Regardless of what problem you are solving an interpretable model will always be preferred because both the end-user and your boss/co-workers can understand what your model is really doing. Model…

How to Interpret Models: PDP and ICE

Towards Data Science

Model interpretability is becoming more valuable. However, when handling large models with complex relationships, interpretation is not an easy task.

Explain Your Model with Microsoft’s InterpretML

Analytics Vidhya

Model interpretability has become the main theme in the machine learning community. Many innovations have burgeoned. The InterpretML module, developed by a team in Microsoft Inc., offers prediction…

When do we need interpretability?

Simply Statistics

I just saw a link to an interesting article by Finale Doshi-Velez and Been Kim titled “Towards A Rigorous Science of Interpretable Machine Learning”. From the abstract: Unfortunately, there is little ...

Interpretable Features in Large Language Models

Towards Data Science

And other interesting tidbits from the new Anthropic Paper “Measurement is the first step that leads to control and eventually to improvement. If you can’t measure something, you can’t understand it....