Technology is getting more and more involved in our lives, and so are algorithms. These algorithms speed up work and reduce workload. Especially machine learning algorithms are improving day by day by imitating human behaviours. Handwriting recognition systems are also stand out on this field. In this study, handwriting digit recognition process has been done with algorithms having different working methods. These algorithms are Support Vector Machine (SVM), Decision Tree, Random Forest, Artificial Neural Networks (ANN), K-Nearest Neighbor (KNN) and K- Means Algorithm. The working logic of the handwriting digit recognition process was examined, and the efficiency of different algorithms on the same database was measured. A report was presented by making comparisons on the accuracy.
Primary Language | English |
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Subjects | Artificial Intelligence |
Journal Section | Research Articles |
Authors | |
Publication Date | February 1, 2021 |
Submission Date | September 29, 2020 |
Acceptance Date | October 30, 2020 |
Published in Issue | Year 2021 Volume: 25 Issue: 1 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.