The modelDown package turns classification or regression models into HTML static websites. With one command you can convert one or more models into a website with visual and tabular model summaries. Summaries like model performance, feature importance, single feature response profiles and basic model audits. The modelDown uses DALEX explainers. So it’s model agnostic (feel … Czytaj dalej modelDown is now on CRAN!
If you could talk to a predictive machine learning model, what would you ask for? Try! Michał Kuźba is developing a mind-blowing project – xai chat-bot. Dialog based system that helps to explore and understand predictive models through natural language conversations (type, speak or phone the model 😉 ). For example, imagine that you have … Czytaj dalej xaibot – conversations with predictive models!
I had amazing weekend in Gdansk thanks to the satRday conference organized by Olgun Aydin, Ania Rybinska and Michal Maj. Together with Hanna Piotrowska we had a talk ,,Machine learning meets design. Design meets machine learning”. Hanna redesigned DALEX visualisations (DALEX is a set of tools for visual explanation of predictive ML models). During the … Czytaj dalej How to design a model visualisation @ Gdansk satRdays
Most people make the mistake of thinking design is what it looks like… People think it’s this veneer — that the designers are handed this box and told, ‚Make it look good!’ That’s not what we think design is. It’s not just what it looks like and feels like. Design is how it works. Steve … Czytaj dalej Make it explainable!
DALEX is a set of tools for explanation, exploration and debugging of predictive models. The nice thing about it is that it can be easily connected to different model factories. Recently Michal Maj wrote a nice vignette how to use DALEX with models created in keras (an open-source neural-network library in python with an R … Czytaj dalej DALEX for keras and parsnip
Do you spend a lot of time on data exploration? If yes, then you will like today’s post about AutoEDA written by Mateusz Staniak. If you ever dreamt of automating the first, laborious part of data analysis when you get to know the variables, print descriptive statistics, draw a lot of histograms and scatter plots … Czytaj dalej Explore the landscape of R packages for automated data exploration
LIME and SHAP are two very popular methods for instance level explanations of machine learning models (XAI). They work nicely for images and text inputs, but share similar weakness in case of tabular data: explanations are additive while complex models are (sometimes) not. iBreakDown addresses this problem. iBreakDown is a a successor of the breakDown … Czytaj dalej iBreakDown: faster, prettier and more precise explanations for predictive models (with interactions)
W najbliższy czwartek o godzinie 18:00 startujemy z 38. spotkaniem Entuzjastów R. Aż trudno uwierzyć, że minęło już 5 lat od naszego pierwszego spotkania w ICMie. Przez te 5 lat gościliśmy ponad 70 prelegentów, często osoby, które znaliśmy z ciekawych blogów, pakietów czy książek. Większość prelegentów pracuje w Warszawie, ale też byli ciekawi goście z … Czytaj dalej To już 5 lat! Gość specjalny na najbliższym SERze opowie o wyjaśnialnym ML