Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

8

ESANN
2006

favoriteEmaildiscussreport

157views Neural Networks» more ESANN 2006»

Data mining techniques for feature selection in blood cell recognition

13 years 6 months ago

Data mining techniques for feature selection in blood cell recognition

Download www.dice.ucl.ac.be

The paper presents and compares the data mining techniques for selection of the diagnostic features in the problem of blood cell recognition in leukemia. Different techniques are compared, including the linear SVM ranking, correlation and statistical analysis of centers and variances of clusters corresponding to different classes. We have applied radial kernel SVM as the classifier. The results of recognition of 10 classes of cells are presented and discussed.

Tomasz Markiewicz, Stanislaw Osowski

Real-time Traffic

Blood Cell Recognition | Data Mining Techniques | ESANN 2006 | ESANN 2007 | Radial Kernel Svm |

claim paper

Related Content

» Visualizing changes in the structure of data for exploratory feature selection

» Efficiently handling feature redundancy in highdimensional data

» Feature selection in scientific applications

» The Electronic Primaries Predicting the US Presidency Using Feature Selection with Safe Da...

» Document clustering via dirichlet process mixture model with feature selection

» GAFacilitated Knowledge Discovery and Pattern Recognition Optimization Applied to the Bioc...

» Rank Aggregation Based Text Feature Selection

» Effective WrapperFilter hybridization through GRASP Schemata

» Creating diverse nearestneighbour ensembles using simultaneous metaheuristic feature selec...

Post Info
More Details (n/a)

Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2006
Where	ESANN
Authors	Tomasz Markiewicz, Stanislaw Osowski

Comments (0)