31 citations · 32 across the 2 of their papers we have counts for
4 papers · 1 filter
Estimating regression errors without ground truth values
Henri Tiittanen, Emilia Oikarinen, Andreas Henelius +1
Regression analysis is a standard supervised machine learning method used to model an outcome variable in terms of a set of predictor variables. In most real-world applications we…
Human-guided data exploration using randomisation
Kai Puolamäki, Emilia Oikarinen, Buse Atli +1
An explorative data analysis system should be aware of what the user already knows and what the user wants to know of the data: otherwise the system cannot provide the user with th…
Human-Guided Data Exploration
Andreas Henelius, Emilia Oikarinen, Kai Puolamäki
The outcome of the explorative data analysis (EDA) phase is vital for successful data analysis. EDA is more effective when the user interacts with the system used to carry out the…
Interpreting Classifiers through Attribute Interactions in Datasets
Andreas Henelius, Kai Puolamäki, Antti Ukkonen
In this work we present the novel ASTRID method for investigating which attribute interactions classifiers exploit when making predictions. Attribute interactions in classification…