Impact of Number of Features Selected and Size of Training Data on the Accuracy of Machine Learning Based Cloud Security Algorithms – An Empirical Analysis
Keywords:
Empirical Analysis, Accuracy Prediction, Features Selected, Training DataAbstract
This study uses Ordinary Least Square (OLS) regression to investigate if the number of features selected and the size of training data are useful in predicting the accuracies obtained in ML based approaches to cloud security.
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