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» Calibrating Random Forests
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ICONIP
2008
13 years 10 months ago
An Evaluation of Machine Learning-Based Methods for Detection of Phishing Sites
In this paper, we present the performance of machine learning-based methods for detection of phishing sites. We employ 9 machine learning techniques including AdaBoost, Bagging, S...
Daisuke Miyamoto, Hiroaki Hazeyama, Youki Kadobaya...
FLAIRS
2006
13 years 10 months ago
Melody Track Identification in Music Symbolic Files
Standard MIDI files contain data that can be considered as a symbolic representation of music (a digital score), and most of them are structured as a number of tracks, one of them...
David Rizo, Pedro J. Ponce de León, Antonio...
NIPS
2004
13 years 10 months ago
Result Analysis of the NIPS 2003 Feature Selection Challenge
The NIPS 2003 workshops included a feature selection competition organized by the authors. We provided participants with five datasets from different application domains and calle...
Isabelle Guyon, Steve R. Gunn, Asa Ben-Hur, Gideon...
CLEF
2010
Springer
13 years 9 months ago
Detection of Visual Concepts and Annotation of Images Using Predictive Clustering Trees
Abstract. In this paper, we present a multiple targets classification system for visual concepts detection and image annotation. Multiple targets classification (MTC) is a variant ...
Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, ...
AAAI
2010
13 years 8 months ago
Fast Conditional Density Estimation for Quantitative Structure-Activity Relationships
Many methods for quantitative structure-activity relationships (QSARs) deliver point estimates only, without quantifying the uncertainty inherent in the prediction. One way to qua...
Fabian Buchwald, Tobias Girschick, Eibe Frank, Ste...