I am writing to you because I need to create a model that tells me whether or not a company will pay its taxes the next month.
For that I have data from 2017 to 2020, with characteristics such as size of the company, type of company, year, month and whether or not it pay taxes in that month and year.
How could I use the year and month features in the model, since I want to use the model to predict which companies will pay in 2021.
I say it's a classification model because the variable to predict is binary (yes or no). If I use the years as categorical data And applied a hotencoder the model could not predict for the year 2021 because it does not exist in the original dataset right?
So how could I use this data to train my classifier?
Because if I do not use the years and I limited myself to using the months. How does the model distinguish the month of January 2020 to the month of January of 2019?