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ICDM
2003
IEEE
143views Data Mining» more  ICDM 2003»
15 years 9 months ago
Active Sampling for Feature Selection
In knowledge discovery applications, where new features are to be added, an acquisition policy can help select the features to be acquired based on their relevance and the cost of...
Sriharsha Veeramachaneni, Paolo Avesani
116
Voted
JIPS
2006
72views more  JIPS 2006»
15 years 3 months ago
A Feature Selection Technique based on Distributional Differences
: This paper presents a feature selection technique based on distributional differences for efficient machine learning. Initial training data consists of data including many featur...
Sung-Dong Kim
143
Voted
BMCBI
2007
133views more  BMCBI 2007»
15 years 3 months ago
MATLIGN: a motif clustering, comparison and matching tool
Background: Sequence motifs representing transcription factor binding sites (TFBS) are commonly encoded as position frequency matrices (PFM) or degenerate consensus sequences (CS)...
Matti Kankainen, Ari Löytynoja
132
Voted
RECSYS
2009
ACM
15 years 10 months ago
Context-based splitting of item ratings in collaborative filtering
Collaborative Filtering (CF) recommendations are computed by leveraging a historical data set of users’ ratings for items. It assumes that the users’ previously recorded ratin...
Linas Baltrunas, Francesco Ricci
142
Voted
ECML
2003
Springer
15 years 8 months ago
Logistic Model Trees
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
Niels Landwehr, Mark Hall, Eibe Frank