harismuneer / Handwritten-Digits-Classification-Using-KNN-Multiclass_Perceptron-SVM

🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.

Date Created 2018-07-03 (6 years ago)

Commits 37 (last one 11 days ago)

Stargazers 62 (0 this week)

Watchers 4 (0 this week)

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Homepage URL: https://github.com/harismuneer

All Topics

knn svm delta-rule mnist-dataset sigmoid-function accuracy-analysis comparative-study efficiency-analysis logistic-regression k-nearest-neighbours multiclass-perceptron support-vector-machines artificial-neural-network support-vector-classifier machine-learning-algorithms supervised-machine-learning handwritten-digit-recognition mnist-classification-logistic perceptron-learning-algorithm learning-algorithms-comparison

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updated: 2024-12-03 @ 08:05am, id: 139596782 / R_kgDOCFIT7g