Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …

Visual analysis of multidimensional data requires expressive and effective ways to reduce
data dimensionality to encode them visually. Multidimensional projections (MDP) figure …

Fusarium species, particularly Fusarium graminearum and F. culmorum, are the main cause
of trichothecene type B contamination in cereals. Data on the distribution of Fusarium …

Visualizations are powerful tools that are commonly used by data scientists to get more
insights about their high dimensional data. One can for example cite t-SNE, which is …

Dimensionality reduction (DR) is frequently used for analyzing and visualizing high-
dimensional data as it provides a good first glance of the data. However, to interpret the DR …

Numerous methods have been described that allow the visualization of the data matrix. But
all suffer from a common problem-observing the data points in the context of the attributes is …

An exemplar is an entity that represents a desirable instance in a multi-attribute
configuration space. It offers certain strengths in some of its attributes without unduly …

In real-world applications when deploying Machine Learning (ML) models, initial model
development includes close analysis of the model results and behavior by a data scientist …

Prioritising maintenance activities in throughput bottlenecks increases the throughput from
the production system. To facilitate the planning and execution of maintenance activities …

Dimensionality reduction techniques are the tools of choice for exploring high-dimensional
datasets by means of low-dimensional projections. However, even state-of-the-art projection …