1 INTRODUCTION

2 MACHINE-LEARNED DISCOVERY THROUGH SUPERVISED CLASSIFICATION
2.1 Training Set of Transient Candidates
2.2 Feature Representation of Candidates
2.3 Random Forest Supervised Classification

3 OPTIMIZING THE DISCOVERY ENGINE

4 APPLICATION OF RB2 TO PTF DATA

5 LABEL CONTAMINATION

6 CONCLUSIONS