Review History


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Summary

  • The initial submission of this article was received on May 4th, 2022 and was peer-reviewed by 2 reviewers and the Academic Editor.
  • The Academic Editor made their initial decision on June 16th, 2022.
  • The first revision was submitted on October 12th, 2022 and was reviewed by 2 reviewers and the Academic Editor.
  • A further revision was submitted on November 9th, 2022 and was reviewed by 1 reviewer and the Academic Editor.
  • The article was Accepted by the Academic Editor on December 22nd, 2022.

Version 0.3 (accepted)

· Dec 22, 2022 · Academic Editor

Accept

I am pleased to say that the authors have addressed the reviewers' main comments and the manuscript is now ready for publication.

[# PeerJ Staff Note - The Academic Editor has advised that Reviewer 2's comments do not need to be addressed.#]

[# PeerJ Staff Note - this decision was reviewed and approved by Claudio Ardagna, a PeerJ Computer Science Section Editor covering this Section #]

Reviewer 2 ·

Basic reporting

no comment

Experimental design

no comment

Validity of the findings

no comment

Additional comments

In this paper, the authors present A game-theoretic model for the classification of selected oil companies' price changes. The paper presents the Nash equilibrium is used as a solution concept to estimate probit parameters for the binary classiûcation problem. A non-cooperative game is proposed in which data variables are players that attempt to maximize their marginal contribution to the log-likelihood function.

1. The Abstract section should summarize in a very concise way the main achievement of the paper. Describe vague ideas about the main results. The authors are instigated to highlight what is new in their studies.
2. The language needs minor review to improve readability.
3. Also in the Introduction, it is important to enhance your motivation. Where the current surveys fail.
4. Authors must develop the framework/architecture of the proposed methods
5. Proposed methods should be compared with the state-of-the-art existing techniques
6. In case to be allowed, it would be interesting authors create a list of abbreviatures.
7. What are the main limitations of the work?
8. Overall, the paper is very well written, and the information is interesting from the field under study. However, some important points need to be take:
a) Bullet 1) is critical, and the authors must highlight and compare with similar papers of the proposal.
9. The quality of the figures needs to be improved.
10. Some of the definitions included in the article should be improved for a better understanding by the reader since some are very basic.
11. Experimental results are not convincing, so authors must give more results to justify their proposal.
12. References: Critical: update it.
Finally, paper needs major improvements

Version 0.2

· Nov 1, 2022 · Academic Editor

Minor Revisions

Kindly incorporate the minor revisions suggested by Reviewer 2.

Reviewer 1 ·

Basic reporting

The authors have very well taken into account the previous comments and concerns, and substantially improved the manuscript. I now recommend it for publication.

Experimental design

The experimental design is adequate and well presented.

Validity of the findings

The results are correct and support the framework present in the paper.

Reviewer 2 ·

Basic reporting

In this paper, the authors present A game-theoretic model for the classiûcation of selected oil companies' price changes. The paper presents he Nash equilibrium is used as a solution concept to estimate probit parameters for the binary classiûcation problem.

Some suggestions to improve the paper are as below:
1.The abstract can be rewritten to be more meaningful. The authors should add more details about their final results in the abstract. Abstract should clarify what is exactly proposed (the technical contribution) and how the proposed approach is validated.
2. Also in the Introduction, Sections must be mentioned in the introduction.
3. What are the main limitations of the work?
4. Proposed methods should be compared with the state-of-the-art existing techniques.
5. Limitations and Highlights of the proposed methods must be addressed properly.
6. Overall, the paper is very well written, and the information is interesting from the field under study. However, some important points need to be take:
a) Bullet 2) is critical, and the authors must highlight and compare with similar papers of the proposal.
7. The conclusion must be improved and avoid redundancy. The conclusion provide some insights into the outcome of the paper. However, I feel that we need further elaboration and critical evaluation within the conclusions.
8. For easy follow-up: A Table should be provided to compare your results with the literature.
9. It is preferable to mention future works in thies paper?
10. The quality of the figures needs to be improved.
11. References: Critical: update it.
Finally, paper needs mainor improvements

Experimental design

no comment

Validity of the findings

no comment

Additional comments

no comment

Version 0.1 (original submission)

· Jun 16, 2022 · Academic Editor

Major Revisions

The reviewers have suggested revising the paper. Kindly go through the reviewers' comments and address the suggestions!

[# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. It is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #]

Reviewer 1 ·

Basic reporting

The authors have presented a game theoretic model for binary classification of price changes in oil companies. For this purpose, a probit classification problem is studied and the parameters in this model are estimated that provides the state of a Nash equilibrium. A stochastic search algorithm, known as the differential evolution, is used to solve for the Nash equilibrium. Finally, numerical experiments using price changes of the Romanian oil company and 2 other oil companies are used to validate the framework.

The paper is technically well-written (except for a few typos like on Page 2, before Eq (2) "ca" should be "can", and space is missing before and after "and" in Eq. (3). )

It is not clear from the introduction about the deficiencies in existing algorithms for game-theoretic classification models that the authors are trying to address. References on several game theoretic approaches are missing (including differential games). Moreover, the introduction starts with Machine Learning approaches but then the discussion shifts to game theoretic approaches. Subsequent discussion on different machine learning approaches for classification are not discussed and made clear, which is misleading. It will be good to have some discussion to highlight the major approach presented in the paper.

The results presented, with both synthetic and real data, are thorough and correct, and the raw codes have been made available as supplementary material.

Experimental design

It is not clear how the authors have improved on the existing literature with their presented method. The classification game and Nash equilibrium concepts are quite classical and well-established. It is important to clearly state the problem at hand, the existing methods available to solve the problem and its deficiencies, and the novelty of the author's contribution.

Validity of the findings

Though the results presented are corrected and can be replicated using the supplementary materials, as per the discussion in the previous sections, the novelty of the work is not clearly mentioned.

Additional comments

No comments.

Reviewer 2 ·

Basic reporting

1. Please explain the abstract of the paper in a better way.
2. The authors didn't write the introduction part appropriately.
3. The aim, method, and problem are not described clearly and scientifically. The equations are not described. The results are not described. Most of the abbreviations are not given. The proposed method is not described.
4. Citation of reference papers is not in order of lines 18, 20, and 22.
5. When citing related work citations that are not done correctly, please rely on recent references.
6. The manuscript needs to be corrected for modifications to the grammar as well as checked.
7. I think the distance between the monitor screen to the respondent's eye should be less than 100 cm.
8. In some parts of the paper, the clarity and editorial quality of the paper are compromised. As a consequence, such parts result in being quite challenging to read. Therefore, I would suggest carefully improving the writing prose to make this paper easier to read.
Bullet 1) is critical, and the authors must highlight and compare with similar papers the proposal.
9. The conclusion must be improved and avoid redundancy.

Experimental design

No comment

Validity of the findings

No comment

Additional comments

No comment

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