Cooling schedules for optimal annealing
Mathematics of Operations Research
Robust trainability of single neurons
Journal of Computer and System Sciences
Journal of Computer and System Sciences
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Local Search in Combinatorial Optimization
Local Search in Combinatorial Optimization
Bounded-depth threshold circuits for computer-assisted CT image classification
Artificial Intelligence in Medicine
Binary and multicategory classification accuracy of the LSA machine
ICCMSE '03 Proceedings of the international conference on Computational methods in sciences and engineering
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We investigate the use of perceptrons for classification of microarray data. Small round blue cell tumours of childhood are difficult to classify both clinically and via routine histology. Khan et al. [10] showed that a system of artificial neural networks can utilize gene expression measurements from microarrays and classify these tumours into four different categories. We used a simulated annealing-based method in learning a system of perceptrons, each obtained by resampling of the training set. Our results are comparable to those of Khan et al., indicating that there is a role for perceptrons in the classification of tumours based on gene expression data. We also show that it is critical to perform feature selection in this type of models.