Search Results for author: Emilia Oikarinen

Found 9 papers, 3 papers with code

Estimating regression errors without ground truth values

no code implementations9 Oct 2019 Henri Tiittanen, Emilia Oikarinen, Andreas Henelius, Kai Puolamäki

Regression analysis is a standard supervised machine learning method used to model an outcome variable in terms of a set of predictor variables.

regression

Guided Visual Exploration of Relations in Data Sets

1 code implementation7 May 2019 Kai Puolamäki, Emilia Oikarinen, Andreas Henelius

This paper proposes a principled framework for interactive visual exploration of relations in data, through views most informative given the user's current knowledge and objectives.

Dimensionality Reduction

Human-guided data exploration using randomisation

1 code implementation20 May 2018 Kai Puolamäki, Emilia Oikarinen, Buse Atli, Andreas Henelius

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 the most informative and useful views of the data.

Human-Guided Data Exploration

no code implementations9 Apr 2018 Andreas Henelius, Emilia Oikarinen, Kai Puolamäki

This framework allows the user to incorporate existing knowledge into the exploration process, focus on exploring a subset of the data, and compare different complex hypotheses concerning relations in the data.

Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach

1 code implementation23 Oct 2017 Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie

We conclude that the information theoretic approach to exploratory data analysis where patterns observed by a user are formalized as constraints provides a principled, intuitive, and efficient basis for constructing an EDA system.

Multivariate Confidence Intervals

no code implementations20 Jan 2017 Jussi Korpela, Emilia Oikarinen, Kai Puolamäki, Antti Ukkonen

In this paper we define confidence intervals for multivariate data that extend the one-dimensional definition in a natural way.

Optimizing Phylogenetic Supertrees Using Answer Set Programming

no code implementations19 Jul 2015 Laura Koponen, Emilia Oikarinen, Tomi Janhunen, Laura Säilä

The supertree construction problem is about combining several phylogenetic trees with possibly conflicting information into a single tree that has all the leaves of the source trees as its leaves and the relationships between the leaves are as consistent with the source trees as possible.

Modularity Aspects of Disjunctive Stable Models

no code implementations15 Jan 2014 Tomi Janhunen, Emilia Oikarinen, Hans Tompits, Stefan Woltran

Practically all programming languages allow the programmer to split a program into several modules which brings along several advantages in software development.

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