Here is my Research Topic: Predicting Bank Failures in USA Here is my Research

Here is my Research Topic:
Predicting Bank Failures in USA
Here is my Research Question:
Which U.S. state is most likely to experience the greatest number of bank failures in the future, and what are the main factors that contribute to this likelihood?
Here is my Dataset
Dataset Name: FDIC Failed Bank List
FDIC Failed Bank List Dataset
Download the FDIC Failed Bank List (CSV)
Here is my chosen ML Method:
Classification machine learning method
Developing the Initial ML Model
During the last two milestones, you may have been thinking about different ways to create a model that explains your thoughts. To complete this milestone, you may have to explore or experiment with different machine learning models. The main objective is to draft your model, explain what you did, and explain why it is the best model for your research question using some metrics. Are you leaving out any variables that could strengthen your model? Are there other machine learning models you might want to implement and try with dataset? Why or why not?

Deliverable
For milestone 3, please ensure you have the following REQUIRED sections ONLY:

Analysis Approach: Describe your analysis, including the Machine Learning model(s) you selected in the context of your final research question, as well as feature engineering, modeling, and performance evaluation.

Please do especially ensure you clearly state your final, possibly revised, research question in a separate sub-section
Preliminary Results: Summarize your results, including suitable performance measures and metrics, and visualizations of the initial results.
Please also ensure you describe any tuning you did to the model.
Next Steps: Describe the final analysis you intend to do, including any potential revisions or additional algorithms you might want to compare and why.
Please address the scale of the problem, model complexity, and which tools you might utilize, as well.
Your submission should include the following:
A clear description of the structure and purpose of the decision tree model that youchoose.
Documentation that refers to potential complications in the analysis process, in an outline or bulleted format. This should be clear, concise, and thorough.
An evaluation of the results of the model which includes discussion of whether or not the results are reasonable and the model is accurate, whether or not there are elements that are not present or are needlessly present, and any errors that may be present.
Guidelines for Submission: Write 2 to 3 double-spaced pages explaining your model(s). Append the graphical representations of your model, and any other supporting material that you feel is necessary to explain this draft model. Include any sources at the end and cite them in APA format. Critical Elements Proficient (100%) Needs Improvement (70%) Not Evident (0%) Value Structure Model and description are clearly structured Model and description are somewhat clearly structured Model and description are not adequately structured 30 Process Documentation Documentation is clear, thorough, and logical Documentation is not fully clear, or leaves unexplained gaps Documentation is not clear 30 Evaluation of Results Evaluation considers reasonableness, accuracy, missing/extraneous elements, and error in the model Evaluation does not fully consider reasonableness, accuracy, missing/extraneous elements, or error in the model Evaluation does not consider reasonableness, accuracy, missing/extraneous elements, or error in the model 30 Articulation of Response Submission has no major errors related to grammar, spelling, syntax, or organization Submission has major errors related to grammar, spelling, syntax, or organization that negatively impact readability and articulation of main ideas Submission has critical errors related to grammar, spelling, syntax, or organization that prevent understanding of ideas 10 Earned Total 100%