WINE
2005
Springer
14 years 2 months ago
2005
Springer
In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...
WILF
2005
Springer
14 years 2 months ago
2005
Springer
Aim of this work is to apply a novel comprehensive machine learning tool for data mining to preprocessing and interpretation of gene expression data. Furthermore, some visualizatio...
SEKE
2005
Springer
14 years 2 months ago
2005
Springer
The constant increase in use of geographic data in different application domains has resulted in large amounts of data stored in spatial databases and in the desire of data mining....
PKDD
2005
Springer
14 years 2 months ago
2005
Springer
This paper presents Weka4WS, a framework that extends the Weka toolkit for supporting distributed data mining on Grid environments. Weka4WS adopts the emerging Web Services Resourc...
PKDD
2005
Springer
14 years 2 months ago
2005
Springer
It is generally believed that data mining results do not violate the anonymity of the individuals recorded in the source database. In fact, data mining models and patterns, in orde...
PAKDD
2005
ACM
14 years 2 months ago
2005
ACM
PAKDD
2005
ACM
14 years 2 months ago
2005
ACM
Abstract. This paper establishes the foundation for the performance measurements of privacy preserving data mining techniques. The performance is measured in terms of the accuracy ...
PAKDD
2005
ACM
14 years 2 months ago
2005
ACM
We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
PAKDD
2005
ACM
14 years 2 months ago
2005
ACM
Density-based clustering has the advantages for (i) allowing arbitrary shape of cluster and (ii) not requiring the number of clusters as input. However, when clusters touch each o...
PAKDD
2005
ACM
14 years 2 months ago
2005
ACM
Abstract. In this paper we present a novel and general framework based on concepts of relational algebra for kernel-based learning over relational schema. We exploit the notion of ...