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.
File Descriptions
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 Descriptions
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)