5 citations · 14 across the 19 of their papers we have counts for
5 papers · 1 filter
Non-linear Visual Knowledge Discovery with Elliptic Paired Coordinates
Rose McDonald, Boris Kovalerchuk
It is challenging for humans to enable visual knowledge discovery in data with more than 2-3 dimensions with a naked eye. This chapter explores the efficiency of discovering predic…
Self-service Data Classification Using Interactive Visualization and Interpretable Machine Learning
Sridevi Narayana Wagle, Boris Kovalerchuk
Machine learning algorithms often produce models considered as complex black-box models by both end users and developers. They fail to explain the model in terms of the domain they…
Discovering Interpretable Machine Learning Models in Parallel Coordinates
Boris Kovalerchuk, Dustin Hayes
This paper contributes to interpretable machine learning via visual knowledge discovery in parallel coordinates. The concepts of hypercubes and hyper-blocks are used as easily unde…
Full interpretable machine learning in 2D with inline coordinates
Boris Kovalerchuk, Hoang Phan
This paper proposed a new methodology for machine learning in 2-dimensional space (2-D ML) in inline coordinates. It is a full machine learning approach that does not require to de…
Deep Learning Image Recognition for Non-images
Boris Kovalerchuk, Divya Chandrika Kalla, Bedant Agarwal
Powerful deep learning algorithms open an opportunity for solving non-image Machine Learning (ML) problems by transforming these problems to into the image recognition problems. Th…