Supervised Learning in Absence of Accurate Class Labels

11:50 am - 12:10 pm

Objective: Guidance
Audience Level: Advanced
Session Type: Presentation

Traditionally supervised learning algorithms are built using labeled training data. However, there are several real world scenarios where the class labels at an instance level may be unavailable. To tackle this challenge, we apply Multi Instance Learning (MIL) algorithms where labels are available at a bag level rather than at an instance level. We motivate the need for MIL algorithms and describe an ensemble based method for the same.


, Research Engineer, IBM Research, Bangalore