In:
American Journal of Advanced Computing, Society for Makers, Artist, Researchers and Technologists, Vol. 1, No. 2 ( 2020-04-01), p. 1-4
Abstract:
This research paper deals with using supervised machine learning algorithms to detect authenticity of bank notes. In this research we were successful in achieving very high accuracy (of the order of 99%) by applying some data preprocessing tricks and then running the processed data on supervised learning algorithms like SVM, Decision Trees, Logistic Regression, KNN. We then proceed to analyze the misclassified points. We examine the confusion matrix to find out which algorithms had more number of false positives and which algorithm had more number of False negatives.
This research paper deals with using supervised machine learning algorithms to detect authenticity of bank notes. In this research we were successful in achieving very high accuracy (of the order of 99%) by applying some data preprocessing tricks and then running the processed data on supervised learning algorithms like SVM, Decision Trees, Logistic Regression, KNN. We then proceed to analyze the misclassified points. We examine the confusion matrix to find out which algorithms had more number of false positives and which algorithm had more number of False negatives.
Type of Medium:
Online Resource
ISSN:
2691-5944
Language:
English
Publisher:
Society for Makers, Artist, Researchers and Technologists
Publication Date:
2020
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