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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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Spring 2015
Cluster analysis plays a very important role for understanding various phenomena about data without any prior knowledge. However, hierarchical clustering algorithms, which are widely used for its representation of data, are computationally expensive. Recently large datasets are prevalent in many...