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» Improving SVM accuracy by training on auxiliary data sources
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IJNSEC
2008
210views more  IJNSEC 2008»
13 years 8 months ago
A Method for Locating Digital Evidences with Outlier Detection Using Support Vector Machine
One of the biggest challenges facing digital investigators is the sheer volume of data that must be searched in locating the digital evidence. How to efficiently locate the eviden...
Zaiqiang Liu, Dongdai Lin, Fengdeng Guo
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
14 years 1 months ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
KDD
2003
ACM
214views Data Mining» more  KDD 2003»
14 years 9 months ago
Adaptive duplicate detection using learnable string similarity measures
The problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. Most existing approaches have relied...
Mikhail Bilenko, Raymond J. Mooney
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
14 years 2 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
ICML
2010
IEEE
13 years 9 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc