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JMLR
2006
132views more  JMLR 2006»
13 years 8 months ago
Learning to Detect and Classify Malicious Executables in the Wild
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
Jeremy Z. Kolter, Marcus A. Maloof
IGARSS
2010
13 years 3 months ago
Calibrating probabilities for hyperspectral classification of rock types
This paper investigates the performance of machine learning methods for classifying rock types from hyperspectral data. The main objective is to test the impact on classification ...
Sildomar T. Monteiro, Richard J. Murphy
ASIAN
2007
Springer
174views Algorithms» more  ASIAN 2007»
14 years 2 months ago
Combining Heterogeneous Classifiers for Network Intrusion Detection
Extensive use of computer networks and online electronic data and high demand for security has called for reliable intrusion detection systems. A repertoire of different classifier...
Ali Borji
ISMIR
2004
Springer
162views Music» more  ISMIR 2004»
14 years 1 months ago
Features and classifiers for the automatic classification of musical audio signals
Several factors affecting the automatic classification of musical audio signals are examined. Classification is performed on short audio frames and results are reported as “ba...
Kristopher West, Stephen Cox
HIS
2008
13 years 10 months ago
Evolutionary Training Set Selection to Optimize C4.5 in Imbalanced Problems
Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
Salvador García, Francisco Herrera