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COLING
2010
13 years 2 months ago
Learning to Predict Readability using Diverse Linguistic Features
In this paper we consider the problem of building a system to predict readability of natural-language documents. Our system is trained using diverse features based on syntax and l...
Rohit J. Kate, Xiaoqiang Luo, Siddharth Patwardhan...
ICML
2003
IEEE
14 years 8 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker
ADMA
2006
Springer
153views Data Mining» more  ADMA 2006»
13 years 9 months ago
An Effective Combination Based on Class-Wise Expertise of Diverse Classifiers for Predictive Toxicology Data Mining
This paper presents a study on the combination of different classifiers for toxicity prediction. Two combination operators for the Multiple-Classifier System definition are also pr...
Daniel Neagu, Gongde Guo, Shanshan Wang
ICITA
2005
IEEE
14 years 1 months ago
Combining Diversity-Based Active Learning with Discriminant Analysis in Image Retrieval
Small-sample learning in image retrieval is a pertinent and interesting problem. Relevance feedback is an active area of research that seeks to find algorithms that are robust wi...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
ICONFERENCE
2011
12 years 11 months ago
Modeling diverse standpoints in text classification: learning to be human by modeling human values
An annotator’s classification of a text not only tells us something about the intent of the text’s author, it also tells us something about the annotator’s standpoint. To un...
Kenneth R. Fleischmann, Thomas Clay Templeton, Jor...