Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Meta-Icvi: Ensemble Validity Metrics For Concise Labeling Of Correct, Under- Or Over-Partitioning In Streaming Clustering, Niklas M. Melton, Sasha A. Petrenko, Donald C. Wunsch
Meta-Icvi: Ensemble Validity Metrics For Concise Labeling Of Correct, Under- Or Over-Partitioning In Streaming Clustering, Niklas M. Melton, Sasha A. Petrenko, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
Understanding the performance and validity of clustering algorithms is both challenging and crucial, particularly when clustering must be done online. Until recently, most validation methods have relied on batch calculation and have required considerable human expertise in their interpretation. Improving real-time performance and interpretability of cluster validation, therefore, continues to be an important theme in unsupervised learning. Building upon previous work on incremental cluster validity indices (iCVIs), this paper introduces the Meta- iCVI as a tool for explainable and concise labeling of partition quality in online clustering. Leveraging a time-series classifier and data-fusion techniques, the Meta- iCVI combines the outputs …
Analysis Of Globule Types In Malignant Melanoma, Jin Xu, Kapil Kumar Gupta, William V. Stoecker, Yamini Krishnamurthy, Harold S. Rabinovitz, Austin Bangert, David A. Calcara, Margaret C. Oliviero, Joseph M. Malters, Rhett J. Drugge, R. Joe Stanley, Randy Hays Moss, Mehmed Emre Celebi
Analysis Of Globule Types In Malignant Melanoma, Jin Xu, Kapil Kumar Gupta, William V. Stoecker, Yamini Krishnamurthy, Harold S. Rabinovitz, Austin Bangert, David A. Calcara, Margaret C. Oliviero, Joseph M. Malters, Rhett J. Drugge, R. Joe Stanley, Randy Hays Moss, Mehmed Emre Celebi
Chemistry Faculty Research & Creative Works
Objective: To identify and analyze subtypes of globules based on size, shape, network connectedness, pigmentation, and distribution to determine which globule types and globule distributions are most frequently associated with a diagnosis of malignant melanoma. Design: Retrospective case series of dermoscopy images with globules. Setting: Private dermatology practices. Participants: Patients in dermatology practices. Intervention: Observation only. Main Outcome Measure: Association of globule types with malignant melanoma. Results: The presence of large globules (odds ratio [OR], 5.25) and globules varying in size (4.72) or shape (5.37) had the highest ORs for malignant melanoma among all globule types and combinations studied. Classical …
Pyrolysis-Mass Spectrometry For Rapid Classification Of Oysters According To Rearing Area, J. Krupcík, P. Oswald, I. Spánik, P. Májek, M. Bajdichová, P. Sandra, Daniel W. Armstrong
Pyrolysis-Mass Spectrometry For Rapid Classification Of Oysters According To Rearing Area, J. Krupcík, P. Oswald, I. Spánik, P. Májek, M. Bajdichová, P. Sandra, Daniel W. Armstrong
Chemistry Faculty Research & Creative Works
Current concern for the safety and traceability of food, as well as the desire of oyster farmers, for marketing reason, to emphasize the geographical origin of their production, requires new methods to make possible a real product identification. In this study, 181 oyster samples were analyzed to determine their origin area. These samples were collected in nine French rearing areas at four different times of the year (spring, summer, and the beginning and end of autumn) and from four to eight sites in each area to provide a variability parameter. Analysis of fingerprints after Curie point pyrolysis-mass spectrometry, by an …
Using The Id3 Symbolic Classification Algorithm To Reduce Data Density, Barry Fiachsbart, Daniel C. St. Clair, Jeff Holland
Using The Id3 Symbolic Classification Algorithm To Reduce Data Density, Barry Fiachsbart, Daniel C. St. Clair, Jeff Holland
Mathematics and Statistics Faculty Research & Creative Works
Effective data reduction is mandatory for modeling complex domains. The work described here demonstrates how to use a symbolic classifier algorithm from machine learning to effectively reduce large amounts of data. The algorithm, Quirdan's ID3, uses input data records and corresponding classifications to produce a decision tree. The resulting tree can be used to classify previously unseen inputs. Alternatively, the attributes found in the tree can be used as the basis to develop other system modeling techniques such as neural networks or mathematical programming algorithms. This approach has been used to effectively reduce data from a large complex domain. The …
Reduced Set Of Phages For Typing Salmonellae, Melvin Gershman, George Markowsky
Reduced Set Of Phages For Typing Salmonellae, Melvin Gershman, George Markowsky
Computer Science Faculty Research & Creative Works
A set composed of 27 phages is described for differentiating Salmonella spp. representative of groups A, B, C1, C2, D1, D2, E1, E2, E3, E4, G1, K, and N. All of the 1,245 cultures used in this effort were typable and were differentiated on the basis of the 420 phage patterns observed. All results were reproducible. Characteristic phage patterns were produced by a variety of Salmonella serovars isolated from campus incidents and a number of hospital, family, restaurant, and processing plant outbreaks …