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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

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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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