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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
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3000
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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