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JMLR
2008
117views more  JMLR 2008»
14 years 10 months ago
Closed Sets for Labeled Data
Closed sets have been proven successful in the context of compacted data representation for association rule learning. However, their use is mainly descriptive, dealing only with ...
Gemma C. Garriga, Petra Kralj, Nada Lavrac
3DIM
2007
IEEE
15 years 2 months ago
Aerial Lidar Data Classification using AdaBoost
We use the AdaBoost algorithm to classify 3D aerial lidar scattered height data into four categories: road, grass, buildings, and trees. To do so we use five features: height, hei...
Suresh K. Lodha, Darren N. Fitzpatrick, David P. H...
ISBI
2006
IEEE
15 years 10 months ago
A multiresolution enhancement to generic classifiers of subcellular protein location images
We propose an algorithm for the classification of fluorescence microscopy images depicting the spatial distribution of proteins within the cell. The problem is at the forefront of...
Thomas E. Merryman, Keridon Williams, Gowri Sriniv...
SAC
2006
ACM
15 years 4 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
BMCBI
2006
140views more  BMCBI 2006»
14 years 10 months ago
Feature selection using Haar wavelet power spectrum
Background: Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification using microarrays. Statistical m...
Prabakaran Subramani, Rajendra Sahu, Shekhar Verma