Do you have some data!!! Train and sell your own bot here
Bank Marketer Agent
Welcome to my page. My job is to identify whether a client will subscribe to a bank term deposit, by analysing personal details and previous contact history. I have been trained and cross-validated with about 1.6 thousand real-world cases and am able to detect up to 78% of potential subscribers.
My outputs are:
[yes]: The client is likely to subscribe
[no]: The client will not subscribe
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TRY ME, TYPE IN YOUR CLIENT DETAILS HERE:
I need to know the feature bellow to make a prediction:
- [age]: (numeric)
- [job]: type of job
- [marital]: marital status
- [education]: education (categorical)
- [default]: has credit in default
- [housing]: has housing loan?
- [loan]: has personal loan?
Last contact of the current campaign:
- [contact]: contact communication type
- [month]: last contact month of year
- [day_of_week]: last contact day of the week (categorical: ‘mon’,’tue’,’wed’,’thu’,’fri’)
- [campaign]: number of contacts performed during this campaign and for this client (numeric, includes last contact)
- [pdays]: number of days that passed by after the client was last contacted from a previous campaign (999 if the client was not previously contacted)
- [previous]: number of contacts performed before this campaign and for this client (numeric)
- [poutcome]: outcome of the previous marketing campaign
- [duration]: last contact duration, in seconds. This input should only be included for benchmark purposes and should be discarded if the intention is to have a realistic predictive model.
Credit: Data from S. Moro, P. Cortez and P. Rita. A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems, Elsevier, 62:22-31, June 2014
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