5 papers
Clustering with Uniformity- and Neighbor-Based Random Geometric Graphs
Rui Shi, Elvan Ceyhan, Nedret Billor
We propose a graph-based clustering method based on Cluster Catch Digraphs (CCDs) that extends their applicability to moderate-dimensional data settings. Existing CCD variants, suc…
Outlyingness Scores with Cluster Catch Digraphs
Rui Shi, Elvan Ceyhan, Nedret Billor
This paper introduces two novel, outlyingness scores (OSs) based on Cluster Catch Digraphs (CCDs): Outbound Outlyingness Score (OOS) and Inbound Outlyingness Score (IOS). These sco…
Outlier Detection with Cluster Catch Digraphs
Rui Shi, Nedret Billor, Elvan Ceyhan
This paper introduces a novel family of outlier detection algorithms based on Cluster Catch Digraphs (CCDs), specifically tailored to address the challenges of high dimensionality…
Enhancing Electrocardiography Data Classification Confidence: A Robust Gaussian Process Approach (MuyGPs)
Ukamaka V. Nnyaba, Hewan M. Shemtaga, David W. Collins +3
Analyzing electrocardiography (ECG) data is essential for diagnosing and monitoring various heart diseases. The clinical adoption of automated methods requires accurate confidence…
Stellar Blend Image Classification Using Computationally Efficient Gaussian Processes
Chinedu Eleh, Yunli Zhang, Rafael Bidese +4
Stellar blends, where two or more stars appear blended in an image, pose a significant visualization challenge in astronomy. Traditionally, distinguishing these blends from single…