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Showing 1 to 3 of 3 for “"Nearest neighbour methods"”.
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Modern k-Nearest Neighbour Methods in Entropy Estimation, Independence Testing and Classification
Nearest neighbour methods are a classical approach in nonparametric statistics. The k-nearest neighbour classifier can be traced back to the seminal work of Fix and Hodges (1951) and they also enjoy popularity in many other problems including density estimation and regression. In this thesis we …
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Biologically-Interpretable Disease Classification Based on Gene Expression Data
… classifiers like support vector machines, nearest-neighbour methods, and boosting have been applied successfully to this problem. However, it is difficult to determine from these classifiers which genes are responsible for the distinctions between the diseases. We propose a novel framework …
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Using CBR to improve the usability of numerical models
… over nominal values, termed Generalised Shepard Nearest Neighbour method (GSNN). GSNN can utilise distance metrics defined on the solution space of a CBR system. The properties and advantages of GSNN are examined in the thesis. A comparison is made with other CBR retrieval methods, using several …