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» MCA Based Performance Evaluation of Project Selection
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ICCV
2009
IEEE
16 years 4 months ago
Efficient subset selection based on the Renyi entropy
Many machine learning algorithms require the summation of Gaussian kernel functions, an expensive operation if implemented straightforwardly. Several methods have been proposed t...
Vlad I. Morariu1, Balaji V. Srinivasan, Vikas C. R...
AI
2004
Springer
14 years 11 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu
AVSS
2009
IEEE
15 years 4 months ago
Comparative Evaluation of Stationary Foreground Object Detection Algorithms Based on Background Subtraction Techniques
In several video surveillance applications, such as the detection of abandoned/stolen objects or parked vehicles, the detection of stationary foreground objects is a critical task...
Álvaro Bayona, Juan Carlos San Miguel, Jos&...
DMIN
2006
158views Data Mining» more  DMIN 2006»
15 years 26 days ago
Ensemble Selection Using Diversity Networks
- An ideal ensemble is composed of base classifiers that perform well and that have minimal overlap in their errors. Eliminating classifiers from an ensemble based on a criterion t...
Qiang Ye, Paul W. Munro
CORR
2011
Springer
200views Education» more  CORR 2011»
14 years 6 months ago
Using Feature Weights to Improve Performance of Neural Networks
Different features have different relevance to a particular learning problem. Some features are less relevant; while some very important. Instead of selecting the most relevant fe...
Ridwan Al Iqbal