TY  - JOUR
TI  - Handwritten Digit Recognition Using Machine Learning
AB  - Technology is getting more and more involved in our lives, and so are algorithms. Thesealgorithms speed up work and reduce workload. Especially machine learning algorithms areimproving day by day by imitating human behaviours. Handwriting recognition systems arealso stand out on this field. In this study, handwriting digit recognition process has been donewith algorithms having different working methods. These algorithms are Support VectorMachine (SVM), Decision Tree, Random Forest, Artificial Neural Networks (ANN), K-NearestNeighbor (KNN) and K- Means Algorithm. The working logic of the handwriting digitrecognition process was examined, and the efficiency of different algorithms on the samedatabase was measured. A report was presented by making comparisons on the accuracy.
AU  - Karakaya, Rabia
AU  - Çakar, Serap
DO  - 10.16984/saufenbilder.801684
PY  - 2021
JO  - Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi
VL  - 25
IS  - 1
SN  - 1301-4048
SP  - 65
EP  - 71
DB  - TRDizin
UR  - http://search/yayin/detay/420212
ER  -