53 citations · 108 across the 11 of their papers we have counts for
12 papers
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…
Guided Visual Exploration of Relations in Data Sets
Kai Puolamäki, Emilia Oikarinen, Andreas Henelius
Efficient explorative data analysis systems must take into account both what a user knows and wants to know. This paper proposes a principled framework for interactive visual explo…
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…
Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach
Kai Puolamäki, Emilia Oikarinen, Bo Kang +2
Visual exploration of high-dimensional real-valued datasets is a fundamental task in exploratory data analysis (EDA). Existing methods use predefined criteria to choose the represe…
Subjectively Interesting Subgroup Discovery on Real-valued Targets
Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn +3
Deriving insights from high-dimensional data is one of the core problems in data mining. The difficulty mainly stems from the fact that there are exponentially many variable combin…