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The Response to the first reviewer's comments 1. The 1st comment: You should mention the author not just only another study. It will ease the reader to know who is the author of the statement Modification: Before modification Another study [7] was conducted to find the most efficient and accurate data mining algorithm for target marketing. This study selected 14 algorithms to compare processing cost, accuracy, Type I error rate, and Type II error rate. The dataset used in the experiment was taken from a Portuguese direct marketing campaign related to a bank deposit subscription. The result of this experiment was that Multinomial Naïve Bayes is still the ideal algorithm in the domain of bank term deposit prediction. The next paper [8] discusses classification mechanisms for data streams. Data streams contain a high volume of multi-dimensional, unlabeled data generated in environments such as stock markets, astronomical applications, weblogs, clickstreams, flood, fire and police corps monitoring. The proposed method took a novel approach towards classification of data streams through applying unsupervised classification techniques such as clustering followed by a supervised classifier such as Support Vector Machine. After modification: Liu et al. [7] was conducted to find the most efficient and accurate data mining algorithm for target marketing. This study selected 14 algorithms to compare processing cost, accuracy, Type I error rate, and Type II error rate. The dataset used in the experiment was taken from a Portuguese direct marketing campaign related to a bank deposit subscription. The result of this experiment was that Multinomial Naïve Bayes is still the ideal algorithm in the domain of bank term deposit prediction. M. A. Khan & A. Khan [8] discusses classification mechanisms for data streams. Data streams contain a high volume of multi-dimensional, unlabeled data generated in environments such as stock markets, astronomical applications, weblogs, clickstreams, flood, fire and police corps monitoring. The proposed method took a novel approach towards classification of data streams through applying unsupervised classification techniques such as clustering followed by a supervised classifier such as Support Vector Machine. 2. The 2nd Comment : You should choose which one you will present to the reader, the graph or the numbers in the table . Modification : Before modification : Feature Number 3500 3000 2500 2000 1500 1000 500 0 1019 2029 3039 4049 5059 6069 7079 8089 3310 106 16 6 1 2 0 0 0 0 2 1-9 Computer 90>100 99 Mobile Phone 2795 76 17 7 1 1 4 3 0 2 2 Camera 90 22 2 3 2 1 0 0 0 7 2735 After Modification : 3500 3000 2500 2000 1500 1000 500 0 Computer Mobile Phone Camera