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» Experimental perspectives on learning from imbalanced data
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EPIA
2003
Springer
15 years 3 months ago
Mining Low Dimensionality Data Streams of Continuous Attributes
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
Francisco J. Ferrer-Troyano, Jesús S. Aguil...
ACML
2009
Springer
15 years 2 months ago
Learning Algorithms for Domain Adaptation
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
Manas A. Pathak, Eric Nyberg
ML
2010
ACM
181views Machine Learning» more  ML 2010»
14 years 8 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
15 years 10 months ago
Markov Blankets and Meta-heuristics Search: Sentiment Extraction from Unstructured Texts
Extracting sentiments from unstructured text has emerged as an important problem in many disciplines. An accurate method would enable us, for example, to mine online opinions from ...
Edoardo Airoldi, Xue Bai, Rema Padman
BIOTECHNO
2008
IEEE
15 years 4 months ago
Combining Boundaries and Ratings from Multiple Observers for Predicting Lung Nodule Characteristics
We use the data collected by the Lung Image Database Consortium (LIDC) for modeling the radiologists’ nodule interpretations based on image content of the nodule by using decisi...
Ekarin Varutbangkul, Vesna Mitrovic, Daniela Stan ...