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» From the Nearest Neighbour Rule to Decision Trees
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CATA
2009
15 years 24 days ago
Nearest Shrunken Centroid as Feature Selection of Microarray Data
The nearest shrunken centroid classifier uses shrunken centroids as prototypes for each class and test samples are classified to belong to the class whose shrunken centroid is nea...
Myungsook Klassen, Nyunsu Kim
AMR
2003
Springer
124views Multimedia» more  AMR 2003»
15 years 4 months ago
Adaptive Discovery of Indexing Rules for Video
This paper presents results, at an early stage of research work, of the use of fuzzy decision trees in a multimedia framework. We present the discovery of rules in three different ...
Marcin Detyniecki
PR
2006
80views more  PR 2006»
14 years 11 months ago
Neighborhood size selection in the k-nearest-neighbor rule using statistical confidence
The k-nearest-neighbor rule is one of the most attractive pattern classification algorithms. In practice, the choice of k is determined by the cross-validation method. In this wor...
Jigang Wang, Predrag Neskovic, Leon N. Cooper
NLP
2000
15 years 3 months ago
Learning Rules for Large-Vocabulary Word Sense Disambiguation: A Comparison of Various Classifiers
In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characte...
Georgios Paliouras, Vangelis Karkaletsis, Ion Andr...
KBS
2002
141views more  KBS 2002»
14 years 11 months ago
Using J-pruning to reduce overfitting in classification trees
The automatic induction of classification rules from examples in the form of a decision tree is an important technique used in data mining. One of the problems encountered is the o...
Max Bramer