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The authors addressed all comments accurately, and the manuscript can be accepted.
[# PeerJ Staff Note - this decision was reviewed and approved by Xiangjie Kong, a PeerJ Section Editor covering this Section #]
The authors updated the work.
For final version, review text, formatting and general organization.
It is understood and there is a link to check the information in the repository.
It is understood and there is a link to check the information in the repository.
I believe that the work contributes to the magazine and readers.
The authors have addressed all previous concerns, and hence recommended for publication.
Nil
Nil
Based on the reviewers' comments, the manuscript must be improved before acceptance.
Reviewer 2 has suggested that you cite specific references. You are welcome to add it/them if you believe they are relevant. However, you are not required to include these citations, and if you do not include them, this will not influence my decision.
**PeerJ Staff Note:** It is PeerJ policy that additional references suggested during the peer-review process should only be included if the authors agree that they are relevant and useful.
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The paper titled Label dependency modeling in Multi-Label Naïve Bayes through input space expansion", is a novel writing. The innovation of proposed work lies in its strategic expansion of the input space, which assimilates meta-information derived from the label space, thereby engendering a composite input domain that encompasses both continuous and categorical variables is very interesting. The paper is clearly written in a good style and includes figures and tables wherever necessary.
The authors have clearly acknowledged and identified the contributions of their research against previous researchers' work and presents the proposed approach using rigorous empirical evaluation, utilizing six benchmark datasets.
The purpose of the paper has been very well stated in the abstract but needs clarification on the following:
1. What is the motivation for choosing iMLNB for this particular task?
2. In the discussion section, the research's strengths, limitations, and generality need more appropriate discussions.
The authors adequately evaluated their work, and all claims are clearly articulated and supported by empirical experiments
However, addressing the above comments would improve the quality of the paper. The overall work is good, novel and timely.
The work is interesting but lacks some details and clarifications
I strongly suggest improving the summary and defining just 5 keywords, there are so many keywords included that it looks like a summary of the article.
What does the "B. Notations" table contribute to the introduction and the work as a whole? The relationship and motives are not clear...
The introduction is also not clear what is new in the work (2 recent articles, 1 in 2022 and the other in 2023) out of a total of 41.
This is reflected in the following section II. LITERATURE SURVEY
In this section, I suggest including a comparative table of criteria for this work about the literature research.
I strongly suggest including at least 30% of current references (2022, 2023 and 2024).
Below are recent works with the same theme that can help authors.
https://doi.org/10.3390/bdcc6010008
doi: 10.1109/ACCESS.2023.3255164
https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs223218
**PeerJ Staff Note:** It is PeerJ policy that additional references suggested during the peer-review process should only be included if the authors are in agreement that they are relevant and useful.
I strongly suggest improving the summary and defining just 5 keywords, there are so many keywords included that it looks like a summary of the article.
I'm not sure, more concrete evidence is needed for everything previously described.
What problems do authors encounter in their research?
After all the work done, implementation, testing and results, what problems were resolved?
These contributions are not evident.
The work, if improved, could contribute to the magazine and readers, but as it stands, it needs to be improved.
I hope I have contributed to the authors for future improvements
The following are some serious concerns about this paper. These may be incorporated for further correspondence,
The abstract fails to provide the necessary information about the domain. Only the expert in too specific field may grasp the actual idea. Otherwise, the general CS readers will not get the actual idea.
What is MLB? It is not defined anywhere.
Why do authors provide such in-depth details in the introduction? Again this will cause issues like abstract.
Why equations are provided in the introduction? I think the introduction should provide an overview, of needs, and contributions with any mathematical support. The necessary discussion may be added in the rest of the sections.
There is no need to highlight contributions with specific keywords.
The authors used too many abbreviations in the manuscript, hence, having difficulty understanding texts.
The methodology is well written. However, I suggest authors go through the whole network to symbols and notations.
I suggest strategies to avoid using too many of those equations without needs.
It is better to include some graphs to show the figure-wise result. It will attract readers with more attention.
Included in basic reportings
Included in basic reportings
Included in basic reportings
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