A classification function maps a set of vectors into several classes. machine learning problem is treated as design for partially defined functions. To realize functions MNIST hand written digits, three different architectures are considered: Single-unit realization, 45-unit and ×r realization. The realization consists 45 ternary classifiers, 10 counters, max selector. Test accuracy these compa...

Technology is getting more and involved in our lives, so are algorithms. These algorithms speed up work reduce workload. Especially machine learning improving day by imitating human behaviours. Handwriting recognition systems also stand out on this field. In study, handwriting digit process has been done with having different working methods. Support Vector Machine (SVM), Decision Tree, Random ...

This paper discusses a methodology for handwritten character recognition applying feature subset selection to reduce number of features. Its novelty lies in the use of a genetic algorithm for the preparation of input data for a support vector machine which is employed to recognize the handwritten Persian digits in particular. Comprehensive experiments on handwritten Persian digits demonstrate t...

Handwritten digit recognition is an open problem in computer vision and pattern recognition, and solving this problem has elicited increasing interest. The main challenge of this problem is the design of an efficient method that can recognize the handwritten digits that are submitted by the user via digital devices. Numerous studies have been proposed in the past and in recent years to improve ...