An investor is any person or other entity (such as a firm or mutual fund) who commits capital with the expectation of receiving financial returns. Investors utilize investments in order to grow their money and/or provide an income during retirement,

A term investment is a fixed-term investment that includes the deposit of money into an account at a financial institution. Term deposit investments usually carry short-term maturities ranging from one month to a few years and will have varying levels of required minimum deposits.

Assume a retail bank wants to study the success of telemarketing calls for selling the bank's long-term deposits. We solved it by using some data mining (and machine learning) tools for this purpose. Dataset collected is a large dataset comprising of 11,755 instances with 16 + output = 17 attributes.

The classification goal is to predict if the client will subscribe a term deposit (variable no. 17:y) based on the remaining 16 attributes.

The dataset has been nicely split into train/dev/test partitions and is available to you.

The description of the 17 attributes of dataset are as follows:

Input variables consisting of background data from the bank’s 11,755 clients: 1 - age 2 - job : type of job 3 -marital:maritalstatus 4 -education 5 - default: has credit in default? 6 -balance:averageyearlybalance,ineuros 7 - housing: has housing loan? 8 - loan: has personal loan?

The following attributes are related with the last contact of the current telemarketing campaign: 9 - contact: contact communication type 10-day:lastcontactdayofthemonth 11-month:lastcontactmonthofyear 12 -duration:lastcontactduration,inseconds

Other recorded attributes are:

13 - campaign: number of contacts performed during this campaign and forthis client 14-pdays:numberofdaysthatpassedbyaftertheclientwaslastcontactedfroma previous campaign (-1 means client was not previously contacted) 15 - previous: number of contacts performed before this campaign and forthis client 16 - poutcome: outcome ofthe previous marketing campaign Output variable (desired target): 17 - y - has the client subscribed a term deposit?

The Decision Trees and k-Nearest Neighbours algorithms are used in order to train models to perform a binary classification task on a dataset about a bank’s long-term deposits.

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

Open Source