31 search results - page 4 / 7 » The Effect of Principal Component Analysis on Machine Learni... |
ADBIS
2003
Springer
14 years 22 days ago
2003
Springer
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble...
ICDM
2007
IEEE
13 years 11 months ago
2007
IEEE
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
ACMACE
2008
ACM
13 years 9 months ago
2008
ACM
Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
ICIP
2003
IEEE
14 years 9 months ago
2003
IEEE
In this paper, an efficient method using various histogrambased (high-dimensional) image content descriptors for automatically classifying general color photos into relevant categ...
ICIAR
2004
Springer
14 years 26 days ago
2004
Springer
Previous work has shown that principal component analysis (PCA) of three-dimensional face models can be used to perform recognition to a high degree of accuracy. However, experimen...