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ACL
2010
13 years 6 months ago
Fine-Grained Genre Classification Using Structural Learning Algorithms
Prior use of machine learning in genre classification used a list of labels as classification categories. However, genre classes are often organised into hierarchies, e.g., coveri...
Zhili Wu, Katja Markert, Serge Sharoff
ICPR
2004
IEEE
14 years 9 months ago
Feature Subset Selection using ICA for Classifying Emphysema in HRCT Images
Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...
Mithun Nagendra Prasad, Arcot Sowmya, Inge Koch
CIKM
2008
Springer
13 years 10 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
PRIB
2010
Springer
242views Bioinformatics» more  PRIB 2010»
13 years 7 months ago
Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis
Abstract. Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous...
Scott Doyle, Anant Madabhushi
LREC
2008
128views Education» more  LREC 2008»
13 years 10 months ago
Relation between Agreement Measures on Human Labeling and Machine Learning Performance: Results from an Art History Domain
We discuss factors that affect human agreement on a semantic labeling task in the art history domain, based on the results of four experiments where we varied the number of labels...
Rebecca J. Passonneau, Thomas Lippincott, Tae Yano...