Model Interpretability - Learn Data Science with Travis

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...

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…

How to Increase the Interpretability of Your Predictive Model

Towards Data Science

Accuracy and interpretability are said to be diametrically different. Complex models tend to achieve the highest accuracies, while simpler models tend to be more interpretable. But what if we want to…...

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…

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…

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 ...

Importance of Interpretability

Christophm Interpretable Machine Learning Book

If a machine learning model performs well, why do we not just trust the model and ignore why it made a certain decision? “The problem is that a single metric, such as classification accuracy, is an in...

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…

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…

Which models are interpretable?

Towards Data Science

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

Anchor your Model Interpretation by Anchors

Towards Data Science

Model interpretation means providing reason and the logic behind in order to enable the accountability and transparency on model. As mentioned in previous blog (Introduction to Model Interpretation…