I have dataset which contains job application history of few workers.
Usecase : workers apply for job on my organizations. I approve the request looking at his skills. I want to create model which can help me to predict best possible location_id based on historical data. Looking at the historical data of job application and their assigned location ID, we need to create model which can automatically help to recomment location_ID so that we get best acceptance rare.
I have attached sample dataset.
1. Apprach you have used
2. Trying on three different model using sklearn or any other python library
3. Do required pre-processing on data
4. Create model and print accuracy metrics like precision, recall, f1 score
5. Use cross validation to check accuracy
6. Brief explanation on parameters. How they are related using basic graphs
6. Breif documentation
When you bid for the project. Write me what approach will you use and how you are planning to crack this