Answers.Body: <p>One approach you could take is to use a supervised learning algorithm to train a model on past budget data in order to predict which items are likely to be funded in the current budget year. This would require labelling the data with a binary label indicating whether or not each item was funded in each budget year. You could then use this labelled data to train a classification algorithm such as a logistic regression or a decision tree. Once you have trained your model, you can use it to predict which items are likely to be funded in the current budget year.</p>
  
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Answers.CreationDate: 2022-10-16T22:25:27.180Z
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Body: <p>I am interested in finding references and previous applications where prior year budgets are analyzed to provide guidance for a current year budget.   Specifically, each year some two thousand items are evaluated for funding, with perhaps 500 funded in that year. Information is available in a spreadsheet with multiple parameters that are manually evaluated to determine if an individual item is funded in the budget. I would appreciate any guidance as to how best to make use of such data for say the previous 5 years, where I know what has been funded in those years, to assist in screening items for the current budget year, in particular what approach to ML would be best.  I have attempted a literature search but have not found anything directly relevant.</p>
  <p>Edit:
  Found this reference in my literature search, looks to be applicable:
  <a href="https://www.datacamp.com/courses/case-study-school-budgeting-with-machine-learning-in-python" rel="nofollow noreferrer">https://www.datacamp.com/courses/case-study-school-budgeting-with-machine-learning-in-python</a></p>
  
Tags: <machine-learning><reference-request><binary-classification>
Title: machine learning for a budgeting application
UserDisplayName: rbmales
ThreadText: # machine learning for a budgeting application
  
  (Asked by: username_0 on 2022-10-12)
  
  I am interested in finding references and previous applications where prior year budgets are analyzed to provide guidance for a current year budget. Specifically, each year some two thousand items are evaluated for funding, with perhaps 500 funded in that year. Information is available in a spreadsheet with multiple parameters that are manually evaluated to determine if an individual item is funded in the budget. I would appreciate any guidance as to how best to make use of such data for say the previous 5 years, where I know what has been funded in those years, to assist in screening items for the current budget year, in particular what approach to ML would be best. I have attempted a literature search but have not found anything directly relevant.
  
  Edit:
  Found this reference in my literature search, looks to be applicable:
  <https://www.datacamp.com/courses/case-study-school-budgeting-with-machine-learning-in-python>
  
  **Tags:** machine-learning, reference-request, binary-classification
  
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  ## 1 answers
  
  ### Answer by username_1 on 2022-10-16. Score: 0
  
  One approach you could take is to use a supervised learning algorithm to train a model on past budget data in order to predict which items are likely to be funded in the current budget year. This would require labelling the data with a binary label indicating whether or not each item was funded in each budget year. You could then use this labelled data to train a classification algorithm such as a logistic regression or a decision tree. Once you have trained your model, you can use it to predict which items are likely to be funded in the current budget year.
  
  
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