Local classification and global estimation. Explorations of the k-nearest neighbor algorithm
@inproceedings{Bunt2001LocalCA, title={Local classification and global estimation. Explorations of the k-nearest neighbor algorithm}, author={Harry Bunt and Walter Daelemans and Antal van den Bosch and Iris Hendrickx}, year={2001} }
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References
SHOWING 1-10 OF 125 REFERENCES
C4.5: Programs for Machine Learning
- Computer Science
- 1992
A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.
Machine learning
- Computer ScienceCSUR
- 1996
Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
The Distance-Weighted k-Nearest-Neighbor Rule
- Computer ScienceIEEE Transactions on Systems, Man, and Cybernetics
- 1976
One such classification rule is described which makes use of a neighbor weighting function for the purpose of assigning a class to an unclassified sample.
Toward a universal law of generalization for psychological science.
- Computer ScienceScience
- 1987
A psychological space is established for any set of stimuli by determining metric distances between the stimuli such that the probability that a response learned to any stimulus will generalize to…
A UNIVERSAL PRIOR FOR INTEGERS AND ESTIMATION BY MINIMUM DESCRIPTION LENGTH
- Mathematics
- 1983
of the number of bits required to write down the observed data, has been reformulated to extend the classical maximum likelihood principle. The principle permits estimation of the number of the…
Discriminatory Analysis - Nonparametric Discrimination: Consistency Properties
- Mathematics
- 1989
Abstract : The discrimination problem (two population case) may be defined as follows: e random variable Z, of observed value z, is distributed over some space (say, p-dimensional) either according…