A bit of a deeper look into 5 regression models for the purpose of predicting whether a person will be subscribed or not.
The dataset includes many attributes of a persons socioeconomic and economic status and whether or not they subscribed to a phone plan.
- age: age of person
- job : type of job
- marital : marital status
- education: education level
- default: credit in default
- housing: housing loan
- loan: personal loan
- contact: contact communication type
- month: last contact month of year 10.day_of_week: last contact day of the week
- duration: last contact duration
- campaign: number of contacts performed during the campaign
- pdays: number of days that passed by after the client was last contacted from a previous campaign
- previous: number of contacts performed before the campaign
- poutcome: outcome of the previous marketing campaign
- emp.var.rate: employment variation rate - quarterly indicator
- cons.price.idx: consumer price index - monthly indicator
- cons.conf.idx: consumer confidence index - monthly indicator
- euribor3m: euribor 3 month rate - daily indicator
- nr.employed: number of employees - quarterly indicator
- subscribed - subscribed a term deposit