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Unavoidability of Model Interpretability

Analytics Vidhya

High score model doesn’t mean that it is interpretable, and worse than that, model results could be misleading. Never trust a model that is telling 99% accuracy at the first shot. Tools like LIME…

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 ...

Interpretability and Performance in a Single Model

Towards AI

Machine learning is a discipline full of frictions and tradeoffs but none more important like the balance between accuracy and interpretability. In principle, highly accurate machine learning models…

Tell Me a Story: Thoughts on Model Interpretability

Towards Data Science

Recently, my thinking has circulated around what feel like some of Machine Learning’s biggest meta-conversations: the potential and limitations of learning a generally intelligent actor, the nuance…

Which models are interpretable?

Towards Data Science

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

Interpretability in Machine Learning

Towards Data Science

Should we always trust a model that performs well? A model could reject your application for a mortgage or diagnose you with cancer. The consequences of these decisions are serious and, even if they…

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…

Understanding Machine Learning Interpretability

Towards Data Science

Today, machine learning is everywhere, and although machine learning models have shown a great predictive performance and achieved a notable breakthrough in different applications, those machine…

Edge 251: Global Model-Agnostic Interpretability

TheSequence

In this issue: We explore the concept of global model-agnostic interpretability methods. We review OpenAI’s research about using machine teaching to build interpretable models. We explore the Lucid li...

Interpretable Machine Learning Models

Towards Data Science

A machine learning model from Amazon selected only males from a pile of resumes¹. Another model fired teachers who were underperforming, according to the model². Such models are discriminatory and…

Model Interpretation Strategies

Towards Data Science

This article in a continuation in my series of articles aimed at ‘Explainable Artificial Intelligence (XAI)’. If you haven’t checked out the first article, I would definitely recommend you to take a…

Scope of Interpretability

Christophm Interpretable Machine Learning Book

An algorithm trains a model that produces the predictions. Each step can be evaluated in terms of transparency or interpretability. How does the algorithm create the model? Algorithm transparency is a...

Evaluation of Interpretability

Christophm Interpretable Machine Learning Book

There is no real consensus about what interpretability is in machine learning. Nor is it clear how to measure it. But there is some initial research on this and an attempt to formulate some approaches...

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 ...

Model Complexity, Accuracy and Interpretability

Towards Data Science

Complex Real-world challenges requires complex models to be build to give out predictions with utmost accuracy. However, they do not end up being highly interpretable. In this article, we will be…

Edge 257: Local Model-Agnostic Interpretability Methods

TheSequence

In this issue: Introduce the concept of local model-agnostic interpretability Discuss IBM’s ProfWeight method that combines interpretability and accuracy in a single model. Deep dive into InterpretML,...

The Future of Interpretability

Christophm Interpretable Machine Learning Book

Let us take a look at the possible future of machine learning interpretability. The focus will be on model-agnostic interpretability tools. It is much easier to automate interpretability when it is de...

Increasing Interpretability to Improve Model Robustness

Towards Data Science

A recent attempt to improve the robustness of convolutional neural networks (CNNs) on image classification tasks has revealed an interesting link between robustness and interpretability. Models…

Model Interpretability : ELI5 & Permutation Importance

Analytics Vidhya

How can ELI5 help in explaining a ML model

SHAP: A reliable way to analyze your model interpretability

Towards Data Science

I had started this series of blogs on Explainable AI with 1st understanding what’s the balance between accuracy vs interpretability, then moving on to explaining what are some of the rudimentary…

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 ...

Explainable AI: Interpretability of Machine Learning Models

Towards Data Science

Machine learning models are ubiquitous and becoming a part of our lives more than ever. It is paramount that we can explain the model predictions and can trust them.

Interpretable Machine Learning

Towards Data Science

In his book ‘Interpretable Machine Learning’, Christoph Molnar beautifully encapsulates the essence of ML interpretability through this example: Imagine you are a Data Scientist and in your free time…...