A Case-Based Reasoning Approach for Automatic Adaptation of Classifiers in Mobile Phishing Detection

Table 2

Case description for mobile phishing detection system.

No.	Name	Value
1	Case ID	Case identification number
2	Feature pattern	Combination of feature sets
3	Ensemble methods of classifiers (or) classification algorithm	Boosting/bagging/bayesian (or) algorithm name and their specific parameters
4	Accuracy	Percentage of correct classification
5	Performance	Runtime (seconds)