Search Results for author:
Found 8 papers, 3 papers with code
HUMAP: Hierarchical Uniform Manifold Approximation and Projection
Dimensionality reduction (DR) techniques help analysts understand patterns in high-dimensional spaces.
A Grid-based Method for Removing Overlaps of Dimensionality Reduction Scatterplot Layouts
Dimensionality Reduction (DR) scatterplot layouts have become a ubiquitous visualization tool for analyzing multidimensional datasets.
HardVis: Visual Analytics to Handle Instance Hardness Using Undersampling and Oversampling Techniques
Our proposed system assists users in visually comparing different distributions of data types, selecting types of instances based on local characteristics that will later be affected by the active sampling method, and validating which suggestions from undersampling or oversampling techniques are beneficial for the ML model.
Xtreaming: an incremental multidimensional projection technique and its application to streaming data
To the best of our knowledge, it is the first methodology that is capable of evolving a projection to faithfully represent new emerging structures without the need to store all data, providing reliable results for efficiently and effectively projecting streaming data.
Explainable Matrix -- Visualization for Global and Local Interpretability of Random Forest Classification Ensembles
In this paper, we propose Explainable Matrix (ExMatrix), a novel visualization method for RF interpretability that can handle models with massive quantities of rules.
Q4EDA: A Novel Strategy for Textual Information Retrieval Based on User Interactions with Visual Representations of Time Series
Knowing how to construct text-based Search Queries (SQs) for use in Search Engines (SEs) such as Google or Wikipedia has become a fundamental skill.
Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles
As neural networks become the tool of choice to solve an increasing variety of problems in our society, adversarial attacks become critical.
Multivariate Data Explanation by Jumping Emerging Patterns Visualization
Visual Analytics (VA) tools and techniques have been instrumental in supporting users to build better classification models, interpret models' overall logic, and audit results.
