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Skip to Search Results- 3Data integration
- 3Kernel density estimation
- 1Condition monitoring
- 1Data generator with hierarchical ground truth
- 1Database systems
- 1Density-based clustering
- 1Cheng, Dean
- 1Hong, Sahyun
- 1Khare, Kriti
- 1Liu, Yang
- 1Marcet-Palacios, Marcelo
- 1Serrano Suarez, Diego Fernando
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Integration and Evaluation of Different Kernel Density Estimates in Hierarchical Density-Based Clustering
DownloadFall 2016
Most machine learning methods make assumptions about data. Parametric statistics assume that the data is sampled from a distribution with fixed properties set by the algorithm or user. In contrast, non-parametric statistics do not assume the properties of a distribution. Instead, they assume that...
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Fall 2010
Improved numerical reservoir models are constructed when all available diverse data sources are accounted for to the maximum extent possible. Integrating various diverse data is not a simple problem because data show different precision and relevance to the primary variables being modeled,...
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2008
Zaiane, Osmar, Marcet-Palacios, Marcelo, Sheldon, John, Cheng, Dean
Technical report TR08-13. The vast number of on-line biological and medical databases available can be a great resource for medical researchers. However, the different types of data and interfaces available can be overwhelming for many medical researchers to learn. Moreover, the available...
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Fall 2016
Reliability estimation based on condition monitoring data contains two important parts: thresholding and probability density estimation. Thresholding is to determine a critical level of an indicator corresponding to the transition of system states. Probability density estimation is to estimate...
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Spring 2011
Serrano Suarez, Diego Fernando
Social network sites are becoming increasingly popular and useful as well as relevant means for serious social research. However, despite their user appeal and wide adoption, the current generation of sites are hard to query and explore, offering limited views of local network neighbourhoods....