This work is related to the prediction of unemployment. (unemployment rate forecasting: traditional models vs machine learning techniques). Its main goal is to compare the results of the models through their application on real data (from https:#fred.stlouisfed.org/). This application must be done using RStudio and it is deemed necessary to create tables and diagrams for better visualization of the results. In the `structure’ file I list some of the proposed modules to be analyzed. In red are those that I have already developed and do NOT need to be analyzed by you, while in black are the indicative modules that I would like to be analyzed. The analysis can be done according to the proposed sections/contents (see “structure” file) and with whatever else you consider necessary. Also, along with the text, I would like to be given the corresponding RStudio code that was written, so that I can edit it myself or add various things.
I am sending you the relevant draft file so you can see how I have started. The `structure’ file contains the initial indicative modules around which the theme will be developed.
Some more clarifications:
I am sending you the relevant draft file so you can see how I have started. The `structure’ file contains the initial indicative modules around which the theme will be developed.
Some more clarifications:
1. Everything in red in the `structure` file is already deployed. In black are what is still left.
2. I would like you to initially take care of the data and the application of the methods through the use of RStudio (i.e. the code) to create the comparison tables of the metrics (forecasting accuracy) and the plots with the predictions of the models .
3. Of course I am welcome to discuss changes on the work plan.
4. Thesis size must be up to 15,000 words. I have already written around 6,000 words.