# DataSet Description 

The data is related with direct marketing campaigns of a Health Insurance Company. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to access if the insurance would be ('yes' or 1) or not ('no', or 0) subscribed.


## Files

*   **Insurance_Train.csv** - the training set
*   **Insurance_Test.csv** - the test set
*   **sample_submission.csv** - a sample submission file in the correct format

## Columns

**Client data:**

* `Age` (numeric)
* `Job`: type of job (categorical: 'admin.', 'blue-collar', 'entrepreneur', 'housemaid', 'management', 'retired', 'self-employed', 'services', 'student', 'technician', 'unemployed', 'unknown')
* `Marital`: marital status (categorical: 'divorced', 'married', 'single', 'unknown' ; note: 'divorced' means divorced or widowed)
* `Education`: (categorical: 'basic.4y', 'basic.6y', 'basic.9y', 'high.school', 'illiterate', 'professional.course', 'university.degree', 'unknown')
* `Balance`: average yearly balance, in euros (numeric)
* `Housing`: has housing loan? (categorical: 'no', 'yes', 'unknown')
* `Loan`: has personal loan? (categorical: 'no', 'yes', 'unknown')

**Related with the last contact of the current campaign:**

* `Contact`: contact communication type (categorical:
'cellular','telephone')
* `Month`: last contact month of year (categorical: 'jan', 'feb', 'mar',
…, 'nov', 'dec')
* `Duration`: last contact duration, in seconds (numeric). Important
note: this attribute highly affects the output target (e.g., if
duration=0 then y='no'). Yet, the duration is not known before a call
is performed. Also, after the end of the call y is obviously known.
Thus, this input should only be included for benchmark purposes and
should be discarded if the intention is to have a realistic
predictive model.

**Other attributes:**

* `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 (numeric; 999 means 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 (categorical:
'failure','nonexistent','success')

**Output variable (desired target):**

y - has the client subscribed a term deposit? (binary: 'yes', 'no')