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Table 6 Summary of the results for the experimental model

From: Detecting Denial of Service attacks using machine learning algorithms

  Total instances Correctly classified instances Accuracy Precision Recall Mean Absolute Error Machine Learning Algorithm used Class
Training data 14,063 14,063 100 1.000 1.000 0 Logistic Regression Attack
14,063 13,929 99.04 1.000 0.981 0.007 Naïve Bayes Attack
14,063 14,063 100 1.000 1.000 0 Logistic Regression Normal
14,063 13,929 99.04 0.981 1.000 0.007 Naïve Bayes Normal
Test data 5425 5417 99.85 1.000 0.997 0.0015 Logistic Regression Attack
5425 5385 99.26 1.000 0.985 0.0061 Naïve Bayes Attack
5425 5417 99.85 0.997 1.000 0.0015 Logistic Regression Normal
5425 5385 99.26 0.986 1.000 0.0061 Naïve Bayes Normal
Validation Data 602 601 99.83 1.000 0.997 0.0017 Logistic Regression Attack
602 594 98.67 1.000 0.974 0.0163 Naïve Bayes Attack
602 601 99.83 0.997 1.000 0.0017 Logistic Regression Normal
602 594 98.67 0.974 1.000 0.0163 Naïve Bayes Normal