Influence of various ML-Based Binary Classifiers on the Performance on handwritten digit recognition
This paper aims to produce comparison among four competing Machine Learning classifiers including a boosting algorithm when fitted on MNIST dataset to predict 0-Image. Accuracy (ACC) of Support Vector Machine (SVM), Stochastic Gradient Descent (SGD), AdaBoost and Random Forest models are evaluated through 3-fold and 10-fold Cross Validation. Further, performance is measured through precision (PREC), F1-score (F1), recall (REC), PR Curve and ROC.
Email Address of Submitting Authorfsarain@gmail.com
Submitting Author's InstitutionNUST
Submitting Author's Country