The data consists of real historical data collected from 2010 & 2011. Employees are manually allowed or denied access to resources over time. You must create an algorithm capable of learning from this historical data to predict approval/denial for an unseen set of employees.
train.csv - The training set. Each row has the ACTION (ground truth), RESOURCE, and information about the employee's role at the time of approval
test.csv - The test set for which predictions should be made. Each row asks whether an employee having the listed characteristics should have access to the listed resource.
| Column Name | Description |
| ACTION | ACTION is 1 if the resource was approved, 0 if the resource was not |
| RESOURCE | An ID for each resource |
| MGR_ID | The EMPLOYEE ID of the manager of the current EMPLOYEE ID record; an employee may have only one manager at a time |
| ROLE_ROLLUP_1 | Company role grouping category id 1 (e.g. US Engineering) |
| ROLE_ROLLUP_2 | Company role grouping category id 2 (e.g. US Retail) |
| ROLE_DEPTNAME | Company role department description (e.g. Retail) |
| ROLE_TITLE | Company role business title description (e.g. Senior Engineering Retail Manager) |
| ROLE_FAMILY_DESC | Company role family extended description (e.g. Retail Manager, Software Engineering) |
| ROLE_FAMILY | Company role family description (e.g. Retail Manager) |
| ROLE_CODE | Company role code; this code is unique to each role (e.g. Manager) |