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ML
2000
ACM
15 years 5 months ago
Maximizing Theory Accuracy Through Selective Reinterpretation
Existing methods for exploiting awed domain theories depend on the use of a su ciently large set of training examples for diagnosing and repairing aws in the theory. In this paper,...
Shlomo Argamon-Engelson, Moshe Koppel, Hillel Walt...
ML
2002
ACM
123views Machine Learning» more  ML 2002»
15 years 5 months ago
Feature Generation Using General Constructor Functions
Most classification algorithms receive as input a set of attributes of the classified objects. In many cases, however, the supplied set of attributes is not sufficient for creatin...
Shaul Markovitch, Dan Rosenstein
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
15 years 3 months ago
Evaluating Statistical Tests for Within-Network Classifiers of Relational Data
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
KDD
2009
ACM
210views Data Mining» more  KDD 2009»
16 years 6 months ago
Large-scale behavioral targeting
Behavioral targeting (BT) leverages historical user behavior to select the ads most relevant to users to display. The state-of-the-art of BT derives a linear Poisson regression mo...
Ye Chen, Dmitry Pavlov, John F. Canny
PPSN
1990
Springer
15 years 9 months ago
Feature Construction for Back-Propagation
T h e ease of learning concepts f r o m examples in empirical machine learning depends on the attributes used for describing the training d a t a . We show t h a t decision-tree b...
Selwyn Piramuthu
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