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 …
A survey of surveys on the use of visualization for interpreting machine learning models
A Chatzimparmpas, RM Martins… - Information …, 2020 - journals.sagepub.com
Research in machine learning has become very popular in recent years, with many types of
models proposed to comprehend and predict patterns and trends in data originating from …
models proposed to comprehend and predict patterns and trends in data originating from …
Accountability in algorithmic decision making
N Diakopoulos - Communications of the ACM, 2016 - dl.acm.org
Accountability in algorithmic decision making Page 1 56 COMMUNICATIONS OF THE ACM |
FEBRUARY 2016 | VOL. 59 | NO. 2 practice DOI:10.1145/2844110 Article development led by …
FEBRUARY 2016 | VOL. 59 | NO. 2 practice DOI:10.1145/2844110 Article development led by …
[HTML][HTML] Towards better analysis of machine learning models: A visual analytics perspective
Interactive model analysis, the process of understanding, diagnosing, and refining a
machine learning model with the help of interactive visualization, is very important for users …
machine learning model with the help of interactive visualization, is very important for users …
Manifold: A model-agnostic framework for interpretation and diagnosis of machine learning models
Interpretation and diagnosis of machine learning models have gained renewed interest in
recent years with breakthroughs in new approaches. We present Manifold, a framework that …
recent years with breakthroughs in new approaches. We present Manifold, a framework that …
Visualizing high-dimensional data: Advances in the past decade
Massive simulations and arrays of sensing devices, in combination with increasing
computing resources, have generated large, complex, high-dimensional datasets used to …
computing resources, have generated large, complex, high-dimensional datasets used to …
Visualizing the hidden activity of artificial neural networks
In machine learning, pattern classification assigns high-dimensional vectors (observations)
to classes based on generalization from examples. Artificial neural networks currently …
to classes based on generalization from examples. Artificial neural networks currently …
Approximated and user steerable tSNE for progressive visual analytics
N Pezzotti, BPF Lelieveldt… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Progressive Visual Analytics aims at improving the interactivity in existing analytics
techniques by means of visualization as well as interaction with intermediate results. One …
techniques by means of visualization as well as interaction with intermediate results. One …
Integrating transparency, trust, and acceptance: The intelligent systems technology acceptance model (ISTAM)
ES Vorm, DJY Combs - International Journal of Human–Computer …, 2022 - Taylor & Francis
Intelligent systems such as technologies related to artificial intelligence, robotics, machine
learning, etc. open new insights into data and expand the concept of work in myriad …
learning, etc. open new insights into data and expand the concept of work in myriad …
Considerations for visualizing comparison
M Gleicher - IEEE transactions on visualization and computer …, 2017 - ieeexplore.ieee.org
Supporting comparison is a common and diverse challenge in visualization. Such support is
difficult to design because solutions must address both the specifics of their scenario as well …
difficult to design because solutions must address both the specifics of their scenario as well …