The state of the art in enhancing trust in machine learning models with the use of visualizations
Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …
Toward a quantitative survey of dimension reduction techniques
Dimensionality reduction methods, also known as projections, are frequently used in
multidimensional data exploration in machine learning, data science, and information …
multidimensional data exploration in machine learning, data science, and information …
A taxonomy of visual cluster separation factors
We provide two contributions, a taxonomy of visual cluster separation factors in scatterplots,
and an in‐depth qualitative evaluation of two recently proposed and validated separation …
and an in‐depth qualitative evaluation of two recently proposed and validated separation …
Scatternet: A deep subjective similarity model for visual analysis of scatterplots
Similarity measuring methods are widely adopted in a broad range of visualization
applications. In this work, we address the challenge of representing human perception in the …
applications. In this work, we address the challenge of representing human perception in the …
Large-scale evaluation of topic models and dimensionality reduction methods for 2d text spatialization
Topic models are a class of unsupervised learning algorithms for detecting the semantic
structure within a text corpus. Together with a subsequent dimensionality reduction …
structure within a text corpus. Together with a subsequent dimensionality reduction …
Data‐driven evaluation of visual quality measures
M Sedlmair, M Aupetit - Computer graphics forum, 2015 - Wiley Online Library
Visual quality measures seek to algorithmically imitate human judgments of patterns such as
class separability, correlation, or outliers. In this paper, we propose a novel data‐driven …
class separability, correlation, or outliers. In this paper, we propose a novel data‐driven …
Towards understanding human similarity perception in the analysis of large sets of scatter plots
We present a study aimed at understanding how human observers judge scatter plot
similarity when presented with a large set of iconic scatter plot representations. The work we …
similarity when presented with a large set of iconic scatter plot representations. The work we …
Scagexplorer: Exploring scatterplots by their scagnostics
TN Dang, L Wilkinson - 2014 IEEE Pacific visualization …, 2014 - ieeexplore.ieee.org
A scatter plot displays a relation between a pair of variables. Given a set of v variables, there
are v (v-1)/2 pairs of variables, and thus the same number of possible pair wise scatter plots …
are v (v-1)/2 pairs of variables, and thus the same number of possible pair wise scatter plots …
Sepme: 2002 new visual separation measures
M Aupetit, M Sedlmair - 2016 IEEE pacific visualization …, 2016 - ieeexplore.ieee.org
Our goal is to accurately model human class separation judgements in color-coded
scatterplots. Towards this goal, we propose a set of 2002 visual separation measures, by …
scatterplots. Towards this goal, we propose a set of 2002 visual separation measures, by …
Vizassist: an interactive user assistant for visual data mining
F Bouali, A Guettala, G Venturini - The Visual Computer, 2016 - Springer
We study in this work how a user can be guided to find a relevant visualization in the context
of visual data mining. We present a state of the art on the user assistance in visual and …
of visual data mining. We present a state of the art on the user assistance in visual and …